[GH-ISSUE #9639] Unsupported Value NaN in Ollama log #6290

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opened 2026-04-12 17:43:12 -05:00 by GiteaMirror · 32 comments

GiteaMirror commented 2026-04-12 17:43:12 -05:00

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Originally created by @satya-devloper on GitHub (Mar 11, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9639

Originally assigned to: @mxyng on GitHub.

What is the issue?

llama_model_load: vocab only - skipping tensors
time=2025-03-11T09:41:09.612+05:30 level=DEBUG source=runner.go:741 msg="embedding request" content="{"TASKNAME": "Task1", "STATUS": "FAILED", "SPACE": "spac1", "STARTED TIMESTAMP": "2025-02-20T08:38:12.046Z", "FAILED ISSUE": "No Issue Mentioned", "FAILED DETAILS": "No Details Found", "RESOLUTION STEP": " 'steps'", "TASK COMPLETION DURATION": "5738.378999948502"}"
time=2025-03-11T09:41:09.752+05:30 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=315 used=0 remaining=315
time=2025-03-11T09:41:42.948+05:30 level=INFO source=server.go:915 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"

To Replicate:
curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["Why is the sky blue?","why is the grass green"]}' | jq '.embeddings=[.embeddings[]|length]'

simply trying this curl is also giving same response: unsupported value: NaN

Relevant log output

OS

No response

GPU

No response

CPU

No response

Ollama version

0.5.11

Originally created by @satya-devloper on GitHub (Mar 11, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9639 Originally assigned to: @mxyng on GitHub. ### What is the issue? llama_model_load: vocab only - skipping tensors time=2025-03-11T09:41:09.612+05:30 level=DEBUG source=runner.go:741 msg="embedding request" content="{\"TASKNAME\": \"Task1\", \"STATUS\": \"FAILED\", \"SPACE\": \"spac1\", \"STARTED TIMESTAMP\": \"2025-02-20T08:38:12.046Z\", \"FAILED ISSUE\": \"No Issue Mentioned\", \"FAILED DETAILS\": \"No Details Found\", \"RESOLUTION STEP\": \" 'steps'\", \"TASK COMPLETION DURATION\": \"5738.378999948502\"}" time=2025-03-11T09:41:09.752+05:30 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=315 used=0 remaining=315 time=2025-03-11T09:41:42.948+05:30 level=INFO source=server.go:915 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" To Replicate: curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["Why is the sky blue?","why is the grass green"]}' | jq '.embeddings=[.embeddings[]|length]' simply trying this curl is also giving same response: unsupported value: NaN ### Relevant log output ```shell ``` ### OS _No response_ ### GPU _No response_ ### CPU _No response_ ### Ollama version 0.5.11

GiteaMirror added the bug label 2026-04-12 17:43:12 -05:00

GiteaMirror commented 2026-04-12 17:43:13 -05:00

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@rick-github commented on GitHub (Mar 11, 2025):

$ ollama -v
ollama version is 0.5.11
$ curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["Why is the sky blue?","why is the grass green"]}' | jq '.embeddings=[.embeddings[]|length]'
{
  "model": "nomic-embed-text",
  "embeddings": [
    768,
    768
  ],
  "total_duration": 3523221001,
  "load_duration": 3307812718,
  "prompt_eval_count": 11
}
$ curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["{\"TASKNAME\": \"Task1\", \"STATUS\": \"FAILED\", \"SPACE\": \"spac1\", \"STARTED TIMESTAMP\": \"2025-02-20T08:38:12.046Z\", \"FAILED ISSUE\": \"No Issue Mentioned\", \"FAILED DETAILS\": \"No Details Found\", \"RESOLUTION STEP\": \" '"'"'steps'"'"'\", \"TASK COMPLETION DURATION\": \"5738.378999948502\"}"]}' | jq '.embeddings=[.embeddings[]|length]'
{
  "model": "nomic-embed-text",
  "embeddings": [
    768
  ],
  "total_duration": 420772216,
  "load_duration": 395957210,
  "prompt_eval_count": 110
}

A full server log may aid in debugging.

<!-- gh-comment-id:2713188193 --> @rick-github commented on GitHub (Mar 11, 2025): ```console $ ollama -v ollama version is 0.5.11 $ curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["Why is the sky blue?","why is the grass green"]}' | jq '.embeddings=[.embeddings[]|length]' { "model": "nomic-embed-text", "embeddings": [ 768, 768 ], "total_duration": 3523221001, "load_duration": 3307812718, "prompt_eval_count": 11 } $ curl -s localhost:11434/api/embed -d '{"model":"nomic-embed-text","input":["{\"TASKNAME\": \"Task1\", \"STATUS\": \"FAILED\", \"SPACE\": \"spac1\", \"STARTED TIMESTAMP\": \"2025-02-20T08:38:12.046Z\", \"FAILED ISSUE\": \"No Issue Mentioned\", \"FAILED DETAILS\": \"No Details Found\", \"RESOLUTION STEP\": \" '"'"'steps'"'"'\", \"TASK COMPLETION DURATION\": \"5738.378999948502\"}"]}' | jq '.embeddings=[.embeddings[]|length]' { "model": "nomic-embed-text", "embeddings": [ 768 ], "total_duration": 420772216, "load_duration": 395957210, "prompt_eval_count": 110 } ``` A full server log may aid in debugging.

GiteaMirror commented 2026-04-12 17:43:14 -05:00

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@satya-devloper commented on GitHub (Mar 12, 2025):

time=2025-03-12T10:13:06.067+05:30 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="14.7 GiB" before.free="4.5 GiB" before.free_swap="2.0 GiB" now.total="14.7 GiB" now.free="4.5 GiB" now.free_swap="2.0 GiB"
time=2025-03-12T10:13:06.067+05:30 level=DEBUG source=sched.go:181 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=0x55cc821a7b40 gpu_count=1
time=2025-03-12T10:13:06.167+05:30 level=DEBUG source=sched.go:211 msg="cpu mode with first model, loading"
time=2025-03-12T10:13:06.188+05:30 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="14.7 GiB" before.free="4.5 GiB" before.free_swap="2.0 GiB" now.total="14.7 GiB" now.free="4.5 GiB" now.free_swap="2.0 GiB"
time=2025-03-12T10:13:06.188+05:30 level=INFO source=server.go:100 msg="system memory" total="14.7 GiB" free="4.5 GiB" free_swap="2.0 GiB"
time=2025-03-12T10:13:06.198+05:30 level=DEBUG source=memory.go:107 msg=evaluating library=cpu gpu_count=1 available="[4.5 GiB]"
time=2025-03-12T10:13:06.199+05:30 level=INFO source=memory.go:356 msg="offload to cpu" layers.requested=-1 layers.model=13 layers.offload=0 layers.split="" memory.available="[4.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="352.9 MiB" memory.required.partial="0 B" memory.required.kv="24.0 MiB" memory.required.allocations="[352.9 MiB]" memory.weights.total="240.1 MiB" memory.weights.repeating="195.4 MiB" memory.weights.nonrepeating="44.7 MiB" memory.graph.full="48.0 MiB" memory.graph.partial="48.0 MiB"
time=2025-03-12T10:13:06.200+05:30 level=DEBUG source=server.go:262 msg="compatible gpu libraries" compatible=[]
time=2025-03-12T10:13:06.205+05:30 level=DEBUG source=gpu.go:695 msg="no filter required for library cpu"
time=2025-03-12T10:13:06.206+05:30 level=INFO source=server.go:380 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --ctx-size 8192 --batch-size 512 --verbose --threads 4 --no-mmap --parallel 1 --port 40713"
time=2025-03-12T10:13:06.206+05:30 level=DEBUG source=server.go:398 msg=subprocess environment="[PATH=/opt/gradle/gradle-5.0/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/satya/Desktop/kafka/kafka_2.13-3.2.0/bin:/usr/local/go/bin LD_LIBRARY_PATH=/usr/local/lib/ollama]"
time=2025-03-12T10:13:06.210+05:30 level=INFO source=sched.go:449 msg="loaded runners" count=1
time=2025-03-12T10:13:06.210+05:30 level=INFO source=server.go:557 msg="waiting for llama runner to start responding"
time=2025-03-12T10:13:06.214+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server error"
time=2025-03-12T10:13:06.321+05:30 level=INFO source=runner.go:936 msg="starting go runner"
time=2025-03-12T10:13:06.322+05:30 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(gcc)" threads=4
time=2025-03-12T10:13:06.322+05:30 level=DEBUG source=ggml.go:89 msg="ggml backend load all from path" path=/usr/local/lib/ollama
time=2025-03-12T10:13:06.323+05:30 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:40713"
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-haswell.so score: 0
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-sandybridge.so score: 20
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-sapphirerapids.so score: 0
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-alderlake.so score: 0
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-skylakex.so score: 0
ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-icelake.so score: 0
load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-sandybridge.so
llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = nomic-bert
llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5
llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12
llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048
llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768
llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072
llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12
llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000
llama_model_loader: - kv 8: general.file_type u32 = 1
llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false
llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1
llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000
llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2
llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101
llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102
llama_model_loader: - kv 15: tokenizer.ggml.model str = bert
time=2025-03-12T10:13:06.469+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server loading model"
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "...
llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100
llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 22: tokenizer.ggml.cls_token_id u32 = 101
llama_model_loader: - kv 23: tokenizer.ggml.mask_token_id u32 = 103
llama_model_loader: - type f32: 51 tensors
llama_model_loader: - type f16: 61 tensors
llm_load_vocab: control token: 103 '[MASK]' is not marked as EOG
llm_load_vocab: control token: 0 '[PAD]' is not marked as EOG
llm_load_vocab: control token: 102 '[SEP]' is not marked as EOG
llm_load_vocab: control token: 101 '[CLS]' is not marked as EOG
llm_load_vocab: control token: 100 '[UNK]' is not marked as EOG
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 5
llm_load_vocab: token to piece cache size = 0.2032 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = nomic-bert
llm_load_print_meta: vocab type = WPM
llm_load_print_meta: n_vocab = 30522
llm_load_print_meta: n_merges = 0
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 2048
llm_load_print_meta: n_embd = 768
llm_load_print_meta: n_layer = 12
llm_load_print_meta: n_head = 12
llm_load_print_meta: n_head_kv = 12
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 64
llm_load_print_meta: n_embd_head_v = 64
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 768
llm_load_print_meta: n_embd_v_gqa = 768
llm_load_print_meta: f_norm_eps = 1.0e-12
llm_load_print_meta: f_norm_rms_eps = 0.0e+00
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 3072
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 0
llm_load_print_meta: pooling type = 1
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 2048
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = 137M
llm_load_print_meta: model ftype = F16
llm_load_print_meta: model params = 136.73 M
llm_load_print_meta: model size = 260.86 MiB (16.00 BPW)
llm_load_print_meta: general.name = nomic-embed-text-v1.5
llm_load_print_meta: BOS token = 101 '[CLS]'
llm_load_print_meta: EOS token = 102 '[SEP]'
llm_load_print_meta: UNK token = 100 '[UNK]'
llm_load_print_meta: SEP token = 102 '[SEP]'
llm_load_print_meta: PAD token = 0 '[PAD]'
llm_load_print_meta: CLS token = 101 '[CLS]'
llm_load_print_meta: MASK token = 103 '[MASK]'
llm_load_print_meta: LF token = 0 '[PAD]'
llm_load_print_meta: EOG token = 102 '[SEP]'
llm_load_print_meta: max token length = 21
llm_load_tensors: CPU model buffer size = 260.86 MiB
load_all_data: no device found for buffer type CPU for async uploads
time=2025-03-12T10:13:21.143+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.17"
time=2025-03-12T10:13:22.826+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.18"
time=2025-03-12T10:13:23.367+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.19"
time=2025-03-12T10:13:25.260+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.21"
time=2025-03-12T10:13:26.544+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.22"
time=2025-03-12T10:13:28.172+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.24"
time=2025-03-12T10:13:29.197+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.26"
time=2025-03-12T10:13:30.207+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.28"
time=2025-03-12T10:13:31.723+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.29"
time=2025-03-12T10:13:33.898+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.31"
time=2025-03-12T10:13:34.680+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.33"
time=2025-03-12T10:13:36.195+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.34"
time=2025-03-12T10:13:38.503+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.36"
time=2025-03-12T10:13:39.264+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.38"
time=2025-03-12T10:13:40.022+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.40"
time=2025-03-12T10:13:41.282+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.41"
time=2025-03-12T10:13:43.000+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.43"
time=2025-03-12T10:13:44.834+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.45"
time=2025-03-12T10:13:45.091+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.46"
time=2025-03-12T10:13:45.355+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.46"
time=2025-03-12T10:13:46.866+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.48"
time=2025-03-12T10:13:47.984+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.50"
time=2025-03-12T10:13:50.294+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.52"
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time=2025-03-12T10:14:19.021+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.97"
time=2025-03-12T10:14:19.800+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server not responding"
time=2025-03-12T10:14:20.090+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server loading model"
time=2025-03-12T10:14:20.091+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.98"
llama_new_context_with_model: n_seq_max = 1
llama_new_context_with_model: n_ctx = 8192
llama_new_context_with_model: n_ctx_per_seq = 8192
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: n_ctx_pre_seq (8192) > n_ctx_train (2048) -- possible training context overflow
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 12, can_shift = 1
llama_kv_cache_init: layer 0: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 1: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 2: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 3: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 4: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 5: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 6: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 7: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 8: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 9: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 10: n_embd_k_gqa = 768, n_embd_v_gqa = 768
llama_kv_cache_init: layer 11: n_embd_k_gqa = 768, n_embd_v_gqa = 768
time=2025-03-12T10:14:21.098+05:30 level=DEBUG source=server.go:602 msg="model load progress 1.00"
time=2025-03-12T10:14:21.354+05:30 level=DEBUG source=server.go:605 msg="model load completed, waiting for server to become available" status="llm server loading model"
llama_kv_cache_init: CPU KV buffer size = 288.00 MiB
llama_new_context_with_model: KV self size = 288.00 MiB, K (f16): 144.00 MiB, V (f16): 144.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.00 MiB
llama_new_context_with_model: CPU compute buffer size = 23.00 MiB
llama_new_context_with_model: graph nodes = 453
llama_new_context_with_model: graph splits = 1
time=2025-03-12T10:15:07.541+05:30 level=INFO source=server.go:596 msg="llama runner started in 121.32 seconds"
time=2025-03-12T10:15:07.616+05:30 level=DEBUG source=sched.go:462 msg="finished setting up runner" model=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6
time=2025-03-12T10:15:07.974+05:30 level=DEBUG source=server.go:968 msg="new runner detected, loading model for cgo tokenization"
llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = nomic-bert
llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5
llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12
llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048
llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768
llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072
llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12
llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000
llama_model_loader: - kv 8: general.file_type u32 = 1
llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false
llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1
llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000
llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2
llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101
llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102
llama_model_loader: - kv 15: tokenizer.ggml.model str = bert
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "...
llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100
llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 22: tokenizer.ggml.cls_token_id u32 = 101
llama_model_loader: - kv 23: tokenizer.ggml.mask_token_id u32 = 103
llama_model_loader: - type f32: 51 tensors
llama_model_loader: - type f16: 61 tensors
llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
llm_load_vocab: special tokens cache size = 5
llm_load_vocab: token to piece cache size = 0.2032 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = nomic-bert
llm_load_print_meta: vocab type = WPM
llm_load_print_meta: n_vocab = 30522
llm_load_print_meta: n_merges = 0
llm_load_print_meta: vocab_only = 1
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = all F32
llm_load_print_meta: model params = 136.73 M
llm_load_print_meta: model size = 260.86 MiB (16.00 BPW)
llm_load_print_meta: general.name = nomic-embed-text-v1.5
llm_load_print_meta: BOS token = 101 '[CLS]'
llm_load_print_meta: EOS token = 102 '[SEP]'
llm_load_print_meta: UNK token = 100 '[UNK]'
llm_load_print_meta: SEP token = 102 '[SEP]'
llm_load_print_meta: PAD token = 0 '[PAD]'
llm_load_print_meta: CLS token = 101 '[CLS]'
llm_load_print_meta: MASK token = 103 '[MASK]'
llm_load_print_meta: LF token = 0 '[PAD]'
llm_load_print_meta: EOG token = 102 '[SEP]'
llm_load_print_meta: max token length = 21
llama_model_load: vocab only - skipping tensors
time=2025-03-12T10:15:10.166+05:30 level=DEBUG source=runner.go:741 msg="embedding request" content="{"TASKNAME": "Task1", "STATUS": "FAILED", "SPACE": "spac1", "STARTED TIMESTAMP": "2025-02-20T08:38:12.046Z", "FAILED ISSUE": "No Issue Mentioned", "FAILED DETAILS": "No Details Found", "RESOLUTION STEP": " 'steps'", "TASK COMPLETION DURATION": "5738.378999948502"}"
time=2025-03-12T10:15:10.589+05:30 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=112 used=0 remaining=112
time=2025-03-12T10:15:36.274+05:30 level=INFO source=server.go:915 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
time=2025-03-12T10:15:36.305+05:30 level=ERROR source=routes.go:477 msg="embedding generation failed" error="failed to encode response: json: unsupported value: NaN\n"
[GIN] 2025/03/12 - 10:15:36 | 500 | 2m30s | 127.0.0.1 | POST "/api/embed"
time=2025-03-12T10:15:36.372+05:30 level=DEBUG source=sched.go:466 msg="context for request finished"
time=2025-03-12T10:15:36.381+05:30 level=DEBUG source=sched.go:339 msg="runner with non-zero duration has gone idle, adding timer" modelPath=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 duration=5m0s
time=2025-03-12T10:15:36.383+05:30 level=DEBUG source=sched.go:357 msg="after processing request finished event" modelPath=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 refCount=0

<!-- gh-comment-id:2716568250 --> @satya-devloper commented on GitHub (Mar 12, 2025): time=2025-03-12T10:13:06.067+05:30 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="14.7 GiB" before.free="4.5 GiB" before.free_swap="2.0 GiB" now.total="14.7 GiB" now.free="4.5 GiB" now.free_swap="2.0 GiB" time=2025-03-12T10:13:06.067+05:30 level=DEBUG source=sched.go:181 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=0x55cc821a7b40 gpu_count=1 time=2025-03-12T10:13:06.167+05:30 level=DEBUG source=sched.go:211 msg="cpu mode with first model, loading" time=2025-03-12T10:13:06.188+05:30 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="14.7 GiB" before.free="4.5 GiB" before.free_swap="2.0 GiB" now.total="14.7 GiB" now.free="4.5 GiB" now.free_swap="2.0 GiB" time=2025-03-12T10:13:06.188+05:30 level=INFO source=server.go:100 msg="system memory" total="14.7 GiB" free="4.5 GiB" free_swap="2.0 GiB" time=2025-03-12T10:13:06.198+05:30 level=DEBUG source=memory.go:107 msg=evaluating library=cpu gpu_count=1 available="[4.5 GiB]" time=2025-03-12T10:13:06.199+05:30 level=INFO source=memory.go:356 msg="offload to cpu" layers.requested=-1 layers.model=13 layers.offload=0 layers.split="" memory.available="[4.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="352.9 MiB" memory.required.partial="0 B" memory.required.kv="24.0 MiB" memory.required.allocations="[352.9 MiB]" memory.weights.total="240.1 MiB" memory.weights.repeating="195.4 MiB" memory.weights.nonrepeating="44.7 MiB" memory.graph.full="48.0 MiB" memory.graph.partial="48.0 MiB" time=2025-03-12T10:13:06.200+05:30 level=DEBUG source=server.go:262 msg="compatible gpu libraries" compatible=[] time=2025-03-12T10:13:06.205+05:30 level=DEBUG source=gpu.go:695 msg="no filter required for library cpu" time=2025-03-12T10:13:06.206+05:30 level=INFO source=server.go:380 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --ctx-size 8192 --batch-size 512 --verbose --threads 4 --no-mmap --parallel 1 --port 40713" time=2025-03-12T10:13:06.206+05:30 level=DEBUG source=server.go:398 msg=subprocess environment="[PATH=/opt/gradle/gradle-5.0/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/satya/Desktop/kafka/kafka_2.13-3.2.0/bin:/usr/local/go/bin LD_LIBRARY_PATH=/usr/local/lib/ollama]" time=2025-03-12T10:13:06.210+05:30 level=INFO source=sched.go:449 msg="loaded runners" count=1 time=2025-03-12T10:13:06.210+05:30 level=INFO source=server.go:557 msg="waiting for llama runner to start responding" time=2025-03-12T10:13:06.214+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server error" time=2025-03-12T10:13:06.321+05:30 level=INFO source=runner.go:936 msg="starting go runner" time=2025-03-12T10:13:06.322+05:30 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(gcc)" threads=4 time=2025-03-12T10:13:06.322+05:30 level=DEBUG source=ggml.go:89 msg="ggml backend load all from path" path=/usr/local/lib/ollama time=2025-03-12T10:13:06.323+05:30 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:40713" ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-haswell.so score: 0 ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-sandybridge.so score: 20 ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-sapphirerapids.so score: 0 ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-alderlake.so score: 0 ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-skylakex.so score: 0 ggml_backend_load_best: /usr/local/lib/ollama/libggml-cpu-icelake.so score: 0 load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-sandybridge.so llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = nomic-bert llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5 llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12 llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048 llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768 llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072 llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12 llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000 llama_model_loader: - kv 8: general.file_type u32 = 1 llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1 llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000 llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2 llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101 llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102 llama_model_loader: - kv 15: tokenizer.ggml.model str = bert time=2025-03-12T10:13:06.469+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server loading model" llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "... llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00... llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100 llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102 llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 22: tokenizer.ggml.cls_token_id u32 = 101 llama_model_loader: - kv 23: tokenizer.ggml.mask_token_id u32 = 103 llama_model_loader: - type f32: 51 tensors llama_model_loader: - type f16: 61 tensors llm_load_vocab: control token: 103 '[MASK]' is not marked as EOG llm_load_vocab: control token: 0 '[PAD]' is not marked as EOG llm_load_vocab: control token: 102 '[SEP]' is not marked as EOG llm_load_vocab: control token: 101 '[CLS]' is not marked as EOG llm_load_vocab: control token: 100 '[UNK]' is not marked as EOG llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect llm_load_vocab: special tokens cache size = 5 llm_load_vocab: token to piece cache size = 0.2032 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = nomic-bert llm_load_print_meta: vocab type = WPM llm_load_print_meta: n_vocab = 30522 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 2048 llm_load_print_meta: n_embd = 768 llm_load_print_meta: n_layer = 12 llm_load_print_meta: n_head = 12 llm_load_print_meta: n_head_kv = 12 llm_load_print_meta: n_rot = 64 llm_load_print_meta: n_swa = 0 llm_load_print_meta: n_embd_head_k = 64 llm_load_print_meta: n_embd_head_v = 64 llm_load_print_meta: n_gqa = 1 llm_load_print_meta: n_embd_k_gqa = 768 llm_load_print_meta: n_embd_v_gqa = 768 llm_load_print_meta: f_norm_eps = 1.0e-12 llm_load_print_meta: f_norm_rms_eps = 0.0e+00 llm_load_print_meta: f_clamp_kqv = 0.0e+00 llm_load_print_meta: f_max_alibi_bias = 0.0e+00 llm_load_print_meta: f_logit_scale = 0.0e+00 llm_load_print_meta: n_ff = 3072 llm_load_print_meta: n_expert = 0 llm_load_print_meta: n_expert_used = 0 llm_load_print_meta: causal attn = 0 llm_load_print_meta: pooling type = 1 llm_load_print_meta: rope type = 2 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 1000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 2048 llm_load_print_meta: rope_finetuned = unknown llm_load_print_meta: ssm_d_conv = 0 llm_load_print_meta: ssm_d_inner = 0 llm_load_print_meta: ssm_d_state = 0 llm_load_print_meta: ssm_dt_rank = 0 llm_load_print_meta: ssm_dt_b_c_rms = 0 llm_load_print_meta: model type = 137M llm_load_print_meta: model ftype = F16 llm_load_print_meta: model params = 136.73 M llm_load_print_meta: model size = 260.86 MiB (16.00 BPW) llm_load_print_meta: general.name = nomic-embed-text-v1.5 llm_load_print_meta: BOS token = 101 '[CLS]' llm_load_print_meta: EOS token = 102 '[SEP]' llm_load_print_meta: UNK token = 100 '[UNK]' llm_load_print_meta: SEP token = 102 '[SEP]' llm_load_print_meta: PAD token = 0 '[PAD]' llm_load_print_meta: CLS token = 101 '[CLS]' llm_load_print_meta: MASK token = 103 '[MASK]' llm_load_print_meta: LF token = 0 '[PAD]' llm_load_print_meta: EOG token = 102 '[SEP]' llm_load_print_meta: max token length = 21 llm_load_tensors: CPU model buffer size = 260.86 MiB load_all_data: no device found for buffer type CPU for async uploads time=2025-03-12T10:13:21.143+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.17" time=2025-03-12T10:13:22.826+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.18" time=2025-03-12T10:13:23.367+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.19" time=2025-03-12T10:13:25.260+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.21" time=2025-03-12T10:13:26.544+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.22" time=2025-03-12T10:13:28.172+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.24" time=2025-03-12T10:13:29.197+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.26" time=2025-03-12T10:13:30.207+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.28" time=2025-03-12T10:13:31.723+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.29" time=2025-03-12T10:13:33.898+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.31" time=2025-03-12T10:13:34.680+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.33" time=2025-03-12T10:13:36.195+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.34" time=2025-03-12T10:13:38.503+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.36" time=2025-03-12T10:13:39.264+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.38" time=2025-03-12T10:13:40.022+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.40" time=2025-03-12T10:13:41.282+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.41" time=2025-03-12T10:13:43.000+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.43" time=2025-03-12T10:13:44.834+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.45" time=2025-03-12T10:13:45.091+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.46" time=2025-03-12T10:13:45.355+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.46" time=2025-03-12T10:13:46.866+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.48" time=2025-03-12T10:13:47.984+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.50" time=2025-03-12T10:13:50.294+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.52" time=2025-03-12T10:13:50.546+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.53" time=2025-03-12T10:13:51.303+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.55" time=2025-03-12T10:13:52.323+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.57" time=2025-03-12T10:13:53.426+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.59" time=2025-03-12T10:13:54.393+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.60" time=2025-03-12T10:13:55.477+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.62" time=2025-03-12T10:13:56.511+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.64" time=2025-03-12T10:13:57.019+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.65" time=2025-03-12T10:13:58.039+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.67" time=2025-03-12T10:13:58.293+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.67" time=2025-03-12T10:13:59.315+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.69" time=2025-03-12T10:14:00.113+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.71" time=2025-03-12T10:14:01.397+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.72" time=2025-03-12T10:14:02.080+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.74" time=2025-03-12T10:14:02.342+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.74" time=2025-03-12T10:14:03.105+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.76" time=2025-03-12T10:14:04.127+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.78" time=2025-03-12T10:14:05.000+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.79" time=2025-03-12T10:14:05.508+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.81" time=2025-03-12T10:14:05.830+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.81" time=2025-03-12T10:14:07.138+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.83" time=2025-03-12T10:14:10.006+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.84" time=2025-03-12T10:14:11.335+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.86" time=2025-03-12T10:14:12.354+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.87" time=2025-03-12T10:14:12.607+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.88" time=2025-03-12T10:14:14.600+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.90" time=2025-03-12T10:14:16.579+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.91" time=2025-03-12T10:14:17.433+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.93" time=2025-03-12T10:14:18.251+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.94" time=2025-03-12T10:14:18.756+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.95" time=2025-03-12T10:14:19.021+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.97" time=2025-03-12T10:14:19.800+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server not responding" time=2025-03-12T10:14:20.090+05:30 level=INFO source=server.go:591 msg="waiting for server to become available" status="llm server loading model" time=2025-03-12T10:14:20.091+05:30 level=DEBUG source=server.go:602 msg="model load progress 0.98" llama_new_context_with_model: n_seq_max = 1 llama_new_context_with_model: n_ctx = 8192 llama_new_context_with_model: n_ctx_per_seq = 8192 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 1000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_model: n_ctx_pre_seq (8192) > n_ctx_train (2048) -- possible training context overflow llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 12, can_shift = 1 llama_kv_cache_init: layer 0: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 1: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 2: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 3: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 4: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 5: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 6: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 7: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 8: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 9: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 10: n_embd_k_gqa = 768, n_embd_v_gqa = 768 llama_kv_cache_init: layer 11: n_embd_k_gqa = 768, n_embd_v_gqa = 768 time=2025-03-12T10:14:21.098+05:30 level=DEBUG source=server.go:602 msg="model load progress 1.00" time=2025-03-12T10:14:21.354+05:30 level=DEBUG source=server.go:605 msg="model load completed, waiting for server to become available" status="llm server loading model" llama_kv_cache_init: CPU KV buffer size = 288.00 MiB llama_new_context_with_model: KV self size = 288.00 MiB, K (f16): 144.00 MiB, V (f16): 144.00 MiB llama_new_context_with_model: CPU output buffer size = 0.00 MiB llama_new_context_with_model: CPU compute buffer size = 23.00 MiB llama_new_context_with_model: graph nodes = 453 llama_new_context_with_model: graph splits = 1 time=2025-03-12T10:15:07.541+05:30 level=INFO source=server.go:596 msg="llama runner started in 121.32 seconds" time=2025-03-12T10:15:07.616+05:30 level=DEBUG source=sched.go:462 msg="finished setting up runner" model=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 time=2025-03-12T10:15:07.974+05:30 level=DEBUG source=server.go:968 msg="new runner detected, loading model for cgo tokenization" llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = nomic-bert llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5 llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12 llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048 llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768 llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072 llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12 llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000 llama_model_loader: - kv 8: general.file_type u32 = 1 llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1 llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000 llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2 llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101 llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102 llama_model_loader: - kv 15: tokenizer.ggml.model str = bert llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "... llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00... llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100 llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102 llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 22: tokenizer.ggml.cls_token_id u32 = 101 llama_model_loader: - kv 23: tokenizer.ggml.mask_token_id u32 = 103 llama_model_loader: - type f32: 51 tensors llama_model_loader: - type f16: 61 tensors llm_load_vocab: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect llm_load_vocab: special tokens cache size = 5 llm_load_vocab: token to piece cache size = 0.2032 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = nomic-bert llm_load_print_meta: vocab type = WPM llm_load_print_meta: n_vocab = 30522 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 1 llm_load_print_meta: model type = ?B llm_load_print_meta: model ftype = all F32 llm_load_print_meta: model params = 136.73 M llm_load_print_meta: model size = 260.86 MiB (16.00 BPW) llm_load_print_meta: general.name = nomic-embed-text-v1.5 llm_load_print_meta: BOS token = 101 '[CLS]' llm_load_print_meta: EOS token = 102 '[SEP]' llm_load_print_meta: UNK token = 100 '[UNK]' llm_load_print_meta: SEP token = 102 '[SEP]' llm_load_print_meta: PAD token = 0 '[PAD]' llm_load_print_meta: CLS token = 101 '[CLS]' llm_load_print_meta: MASK token = 103 '[MASK]' llm_load_print_meta: LF token = 0 '[PAD]' llm_load_print_meta: EOG token = 102 '[SEP]' llm_load_print_meta: max token length = 21 llama_model_load: vocab only - skipping tensors time=2025-03-12T10:15:10.166+05:30 level=DEBUG source=runner.go:741 msg="embedding request" content="{\"TASKNAME\": \"Task1\", \"STATUS\": \"FAILED\", \"SPACE\": \"spac1\", \"STARTED TIMESTAMP\": \"2025-02-20T08:38:12.046Z\", \"FAILED ISSUE\": \"No Issue Mentioned\", \"FAILED DETAILS\": \"No Details Found\", \"RESOLUTION STEP\": \" 'steps'\", \"TASK COMPLETION DURATION\": \"5738.378999948502\"}" time=2025-03-12T10:15:10.589+05:30 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=112 used=0 remaining=112 time=2025-03-12T10:15:36.274+05:30 level=INFO source=server.go:915 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" time=2025-03-12T10:15:36.305+05:30 level=ERROR source=routes.go:477 msg="embedding generation failed" error="failed to encode response: json: unsupported value: NaN\n" [GIN] 2025/03/12 - 10:15:36 | 500 | 2m30s | 127.0.0.1 | POST "/api/embed" time=2025-03-12T10:15:36.372+05:30 level=DEBUG source=sched.go:466 msg="context for request finished" time=2025-03-12T10:15:36.381+05:30 level=DEBUG source=sched.go:339 msg="runner with non-zero duration has gone idle, adding timer" modelPath=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 duration=5m0s time=2025-03-12T10:15:36.383+05:30 level=DEBUG source=sched.go:357 msg="after processing request finished event" modelPath=/home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 refCount=0

GiteaMirror commented 2026-04-12 17:43:15 -05:00

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@satya-devloper commented on GitHub (Mar 12, 2025):

@mxyng @rick-github This is the log with debug enabled, I m getting response NaN error

<!-- gh-comment-id:2716569903 --> @satya-devloper commented on GitHub (Mar 12, 2025): @mxyng @rick-github This is the log with debug enabled, I m getting response NaN error

GiteaMirror commented 2026-04-12 17:43:16 -05:00

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@satya-devloper commented on GitHub (Mar 12, 2025):

@rick-github @mxyng , One more thing my ollama is running behind proxy

<!-- gh-comment-id:2716954493 --> @satya-devloper commented on GitHub (Mar 12, 2025): @rick-github @mxyng , One more thing my ollama is running behind proxy

GiteaMirror commented 2026-04-12 17:43:17 -05:00

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@rick-github commented on GitHub (Mar 12, 2025):

This looks pretty normal, except for the model taking two minutes to load. Is the machine virtual or some sort of containerized system, eg proxmox?

<!-- gh-comment-id:2718138782 --> @rick-github commented on GitHub (Mar 12, 2025): This looks pretty normal, except for the model taking two minutes to load. Is the machine virtual or some sort of containerized system, eg proxmox?

GiteaMirror commented 2026-04-12 17:43:19 -05:00

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@satya-devloper commented on GitHub (Mar 13, 2025):

@rick-github its just a linux box hosted in our data center

<!-- gh-comment-id:2720038085 --> @satya-devloper commented on GitHub (Mar 13, 2025): @rick-github its just a linux box hosted in our data center

GiteaMirror commented 2026-04-12 17:43:20 -05:00

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@satya-devloper commented on GitHub (Mar 17, 2025):

@rick-github any update

<!-- gh-comment-id:2728120075 --> @satya-devloper commented on GitHub (Mar 17, 2025): @rick-github any update

GiteaMirror commented 2026-04-12 17:43:22 -05:00

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@rick-github commented on GitHub (Mar 17, 2025):

I am unable to replicate the problem, so need more information.

What's the output of sha256sum home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 ?

Stop the server, restart it, run a test, and post the full log, including the start that shows configuration information and device detection.

<!-- gh-comment-id:2729279845 --> @rick-github commented on GitHub (Mar 17, 2025): I am unable to replicate the problem, so need more information. What's the output of `sha256sum home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6` ? Stop the server, restart it, run a test, and post the full log, including the start that shows configuration information and device detection.

GiteaMirror commented 2026-04-12 17:43:23 -05:00

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@satya-devloper commented on GitHub (Mar 20, 2025):

@rick-github output is : 98e675c8c9e9cd1c71cab9dfca37c83406eba35a4692df55b0fa692f78b29638 sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6

<!-- gh-comment-id:2739032423 --> @satya-devloper commented on GitHub (Mar 20, 2025): @rick-github output is : 98e675c8c9e9cd1c71cab9dfca37c83406eba35a4692df55b0fa692f78b29638 sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6

GiteaMirror commented 2026-04-12 17:43:25 -05:00

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@rick-github commented on GitHub (Mar 20, 2025):

Your model is damaged, it has the wrong sha256 hash. Delete it (ollama rm nomic-embed-text) and re-download it (ollama pull nomic-embed-text).

<!-- gh-comment-id:2739804174 --> @rick-github commented on GitHub (Mar 20, 2025): Your model is damaged, it has the wrong sha256 hash. Delete it (`ollama rm nomic-embed-text`) and re-download it (`ollama pull nomic-embed-text`).

GiteaMirror commented 2026-04-12 17:43:26 -05:00

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@satya-devloper commented on GitHub (Mar 25, 2025):

same issue after that also @rick-github

<!-- gh-comment-id:2751898708 --> @satya-devloper commented on GitHub (Mar 25, 2025): same issue after that also @rick-github

GiteaMirror commented 2026-04-12 17:43:29 -05:00

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@rick-github commented on GitHub (Mar 25, 2025):

Do the sha256 signatures match?

<!-- gh-comment-id:2751902995 --> @rick-github commented on GitHub (Mar 25, 2025): Do the sha256 signatures match?

GiteaMirror commented 2026-04-12 17:43:31 -05:00

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@rick-github commented on GitHub (Mar 25, 2025):

What;s the output of

ls -l /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6

<!-- gh-comment-id:2751913655 --> @rick-github commented on GitHub (Mar 25, 2025): What;s the output of ``` ls -l /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 ```

GiteaMirror commented 2026-04-12 17:43:32 -05:00

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@satya-devloper commented on GitHub (Apr 3, 2025):

output is:
-rw-r--r-- 1 satya satya 274290656 Mar 8 01:40 /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6

<!-- gh-comment-id:2775563422 --> @satya-devloper commented on GitHub (Apr 3, 2025): output is: -rw-r--r-- 1 satya satya 274290656 Mar 8 01:40 /home/satya/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6

GiteaMirror commented 2026-04-12 17:43:33 -05:00

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@rick-github commented on GitHub (Apr 3, 2025):

Do the sha256 signatures match?

<!-- gh-comment-id:2775585283 --> @rick-github commented on GitHub (Apr 3, 2025): Do the sha256 signatures match?

GiteaMirror commented 2026-04-12 17:43:34 -05:00

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@satya-devloper commented on GitHub (Apr 4, 2025):

yes matching

<!-- gh-comment-id:2777628823 --> @satya-devloper commented on GitHub (Apr 4, 2025): yes matching

GiteaMirror commented 2026-04-12 17:43:35 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

I have the same problem

<!-- gh-comment-id:2996258504 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): I have the same problem

GiteaMirror commented 2026-04-12 17:43:36 -05:00

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@rick-github commented on GitHub (Jun 23, 2025):

Have you checked the SHA256 and tried re-downloading the model?

<!-- gh-comment-id:2996295755 --> @rick-github commented on GitHub (Jun 23, 2025): Have you checked the SHA256 and tried re-downloading the model?

GiteaMirror commented 2026-04-12 17:43:37 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

I am on ollama 0.9.2 CU124 bare metal on RTX 4090.

<!-- gh-comment-id:2996312161 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): I am on ollama 0.9.2 CU124 bare metal on RTX 4090.

GiteaMirror commented 2026-04-12 17:43:38 -05:00

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@rick-github commented on GitHub (Jun 23, 2025):

Have you checked the SHA256 and tried re-downloading the model?

<!-- gh-comment-id:2996316288 --> @rick-github commented on GitHub (Jun 23, 2025): Have you checked the SHA256 and tried re-downloading the model?

GiteaMirror commented 2026-04-12 17:43:40 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

Yes I have checked sha and redownloaded anyway. I am using dengcao/Qwen3-Embedding-8B:F16

<!-- gh-comment-id:2996320380 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): Yes I have checked sha and redownloaded anyway. I am using dengcao/Qwen3-Embedding-8B:F16

GiteaMirror commented 2026-04-12 17:43:40 -05:00

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@rick-github commented on GitHub (Jun 23, 2025):

What was the output of the sha sum?

<!-- gh-comment-id:2996323459 --> @rick-github commented on GitHub (Jun 23, 2025): What was the output of the sha sum?

GiteaMirror commented 2026-04-12 17:43:41 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

.ollama/models/blobs$ sha256sum sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055

OUT:
01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055

<!-- gh-comment-id:2996370930 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): .ollama/models/blobs$ sha256sum sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 OUT: 01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055

GiteaMirror commented 2026-04-12 17:43:43 -05:00

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@rick-github commented on GitHub (Jun 23, 2025):

Server logs with OLLAMA_DEBUG=2 will aid in debugging.

<!-- gh-comment-id:2996378678 --> @rick-github commented on GitHub (Jun 23, 2025): [Server logs](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) with `OLLAMA_DEBUG=2` will aid in debugging.

GiteaMirror commented 2026-04-12 17:43:43 -05:00

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@rick-github commented on GitHub (Jun 23, 2025):

The model works with a simple test:

$ ollama -v
ollama version is 0.9.2
$ for i in {1..5} ; do curl -s http://localhost:11434/api/embed -d '{"model":"dengcao/Qwen3-Embedding-8B:F16","input":"Llamas are members of the camelid family"}' | jq -c '.embeddings[]|.[0:3] + ["..."] + .[-3:]' ; done
[0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934]
[0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934]
[0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934]
[0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934]
[0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934]

<!-- gh-comment-id:2996390621 --> @rick-github commented on GitHub (Jun 23, 2025): The model works with a simple test: ``` $ ollama -v ollama version is 0.9.2 $ for i in {1..5} ; do curl -s http://localhost:11434/api/embed -d '{"model":"dengcao/Qwen3-Embedding-8B:F16","input":"Llamas are members of the camelid family"}' | jq -c '.embeddings[]|.[0:3] + ["..."] + .[-3:]' ; done [0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934] [0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934] [0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934] [0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934] [0.00937686,-0.008833623,-0.0025234958,"...",0.013162558,-0.0036315455,0.012727934] ```

GiteaMirror commented 2026-04-12 17:43:44 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

$ for i in {1..5} ; do curl -s http://localhost:11434/api/embed -d '{"model":"dengcao/Qwen3-Embedding-8B:F16","input":"Llamas are members of the camelid family"}' | jq -c '.embeddings[]|.[0:3] + ["..."] + .[-3:]' ; done
[0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551]
[0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551]
[0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551]
[0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551]
[0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551]
$ ollama -v
ollama version is 0.9.2

Seems like ollama is not the problem.

I am using continue.dev, probably there is a problem with the payload sent to be embedded.

<!-- gh-comment-id:2996409862 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): $ for i in {1..5} ; do curl -s http://localhost:11434/api/embed -d '{"model":"dengcao/Qwen3-Embedding-8B:F16","input":"Llamas are members of the camelid family"}' | jq -c '.embeddings[]|.[0:3] + ["..."] + .[-3:]' ; done [0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551] [0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551] [0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551] [0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551] [0.009309137,-0.008815658,-0.0025224872,"...",0.0128948875,-0.0035430363,0.01299551] $ ollama -v ollama version is 0.9.2 Seems like ollama is not the problem. I am using continue.dev, probably there is a problem with the payload sent to be embedded.

GiteaMirror commented 2026-04-12 17:43:45 -05:00

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@NikolasTh90 commented on GitHub (Jun 23, 2025):

I am leaving my debug trace
`Ιουν 23 16:12:49 brainiac ollama[116520]: CUDA driver version: 12.4
Ιουν 23 16:12:49 brainiac ollama[116520]: calling cuDeviceGetCount
Ιουν 23 16:12:49 brainiac ollama[116520]: device count 1
Ιουν 23 16:12:49 brainiac ollama[116520]: time=2025-06-23T16:12:49.946+03:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=/usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01
Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] CUDA totalMem 23995mb
Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] CUDA freeMem 20180mb
Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] Compute Capability 8.9
Ιουν 23 16:12:50 brainiac ollama[116520]: time=2025-06-23T16:12:50.194+03:00 level=DEBUG source=amd_linux.go:419 msg="amdgpu driver not detected /sys/module/amdgpu"
Ιουν 23 16:12:50 brainiac ollama[116520]: releasing cuda driver library
Ιουν 23 16:12:50 brainiac ollama[116520]: time=2025-06-23T16:12:50.194+03:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 library=cuda variant=v12 compute=8.9 driver=12.4 name="NVIDIA GeForce RTX 4090" total="23.4 GiB" available="19.7 GiB"
Ιουν 23 16:12:56 brainiac ollama[116520]: time=2025-06-23T16:12:56.932+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
Ιουν 23 16:12:56 brainiac ollama[116520]: time=2025-06-23T16:12:56.932+03:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="188.5 GiB" before.free="181.1 GiB" before.free_swap="2.0 GiB" now.total="188.5 GiB" now.free="181.0 GiB" now.free_swap="2.0 GiB"
Ιουν 23 16:12:56 brainiac ollama[116520]: initializing /usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuInit - 0x7cff1267ce20
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDriverGetVersion - 0x7cff1267ce40
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetCount - 0x7cff1267ce80
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGet - 0x7cff1267ce60
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetAttribute - 0x7cff1267cf60
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetUuid - 0x7cff1267cec0
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetName - 0x7cff1267cea0
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuCtxCreate_v3 - 0x7cff1267d140
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuMemGetInfo_v2 - 0x7cff12687080
Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuCtxDestroy - 0x7cff126e19c0
Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuInit
Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuDriverGetVersion
Ιουν 23 16:12:56 brainiac ollama[116520]: raw version 0x2f08
Ιουν 23 16:12:56 brainiac ollama[116520]: CUDA driver version: 12.4
Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuDeviceGetCount
Ιουν 23 16:12:56 brainiac ollama[116520]: device count 1
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.070+03:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 name="NVIDIA GeForce RTX 4090" overhead="0 B" before.total="23.4 GiB" before.free="19.7 GiB" now.total="23.4 GiB" now.free="19.7 GiB" now.used="3.7 GiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: releasing cuda driver library
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.070+03:00 level=DEBUG source=sched.go:185 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.077+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=sched.go:228 msg="loading first model" model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[19.7 GiB]"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3.vision.block_count default=0
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 parallel=2 available=21160460288 required="16.8 GiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="188.5 GiB" before.free="181.0 GiB" before.free_swap="2.0 GiB" now.total="188.5 GiB" now.free="181.0 GiB" now.free_swap="2.0 GiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: initializing /usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuInit - 0x7cff1267ce20
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDriverGetVersion - 0x7cff1267ce40
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetCount - 0x7cff1267ce80
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGet - 0x7cff1267ce60
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetAttribute - 0x7cff1267cf60
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetUuid - 0x7cff1267cec0
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetName - 0x7cff1267cea0
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuCtxCreate_v3 - 0x7cff1267d140
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuMemGetInfo_v2 - 0x7cff12687080
Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuCtxDestroy - 0x7cff126e19c0
Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuInit
Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuDriverGetVersion
Ιουν 23 16:12:57 brainiac ollama[116520]: raw version 0x2f08
Ιουν 23 16:12:57 brainiac ollama[116520]: CUDA driver version: 12.4
Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuDeviceGetCount
Ιουν 23 16:12:57 brainiac ollama[116520]: device count 1
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 name="NVIDIA GeForce RTX 4090" overhead="0 B" before.total="23.4 GiB" before.free="19.7 GiB" now.total="23.4 GiB" now.free="19.7 GiB" now.used="3.7 GiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: releasing cuda driver library
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=INFO source=server.go:135 msg="system memory" total="188.5 GiB" free="181.0 GiB" free_swap="2.0 GiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[19.7 GiB]"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3.vision.block_count default=0
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[19.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="16.8 GiB" memory.required.partial="16.8 GiB" memory.required.kv="1.1 GiB" memory.required.allocations="[16.8 GiB]" memory.weights.total="14.1 GiB" memory.weights.repeating="12.9 GiB" memory.weights.nonrepeating="1.2 GiB" memory.graph.full="768.0 MiB" memory.graph.partial="768.0 MiB"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=server.go:284 msg="compatible gpu libraries" compatible="[cuda_v12 cuda_v11]"
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: loaded meta data with 27 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 (version GGUF V3 (latest))
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 0: general.architecture str = qwen3
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 1: general.type str = model
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B Bf16
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 4: general.size_label str = 8B
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 5: qwen3.block_count u32 = 36
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 4096
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 12288
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 32
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 15: general.file_type u32 = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 16: general.quantization_version u32 = 2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 17: tokenizer.ggml.model str = gpt2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 18: tokenizer.ggml.pre str = qwen2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,151665] = ["!", """, "#", "$", "%", "&", "'", ...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 20: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 21: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 22: tokenizer.ggml.eos_token_id u32 = 151645
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 151643
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 24: tokenizer.ggml.bos_token_id u32 = 151643
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 25: tokenizer.ggml.add_bos_token bool = false
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 26: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f32: 145 tensors
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f16: 253 tensors
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file format = GGUF V3 (latest)
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file type = F16
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file size = 14.10 GiB (16.00 BPW)
Ιουν 23 16:12:57 brainiac ollama[116520]: init_tokenizer: initializing tokenizer for type 2
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151660 '<|fim_middle|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151659 '<|fim_prefix|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151653 '<|vision_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151648 '<|box_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151646 '<|object_ref_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151649 '<|box_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151655 '<|image_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151651 '<|quad_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151647 '<|object_ref_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151652 '<|vision_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151654 '<|vision_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151656 '<|video_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151644 '<|im_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151661 '<|fim_suffix|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151650 '<|quad_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: special tokens cache size = 22
Ιουν 23 16:12:57 brainiac ollama[116520]: load: token to piece cache size = 0.9310 MB
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: arch = qwen3
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab_only = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model type = ?B
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model params = 7.57 B
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: general.name = Qwen3 Embedding 8B Bf16
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab type = BPE
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_vocab = 151665
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_merges = 151387
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: BOS token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOS token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOT token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: PAD token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: LF token = 198 'Ċ'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM MID token = 151660 '<|fim_middle|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM REP token = 151663 '<|repo_name|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SEP token = 151664 '<|file_sep|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151662 '<|fim_pad|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151663 '<|repo_name|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151664 '<|file_sep|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: max token length = 256
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_load: vocab only - skipping tensors
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:360 msg="adding gpu library" path=/usr/local/lib/ollama/cuda_v12
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:367 msg="adding gpu dependency paths" paths=[/usr/local/lib/ollama/cuda_v12]
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:431 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 --ctx-size 8192 --batch-size 512 --n-gpu-layers 37 --threads 8 --parallel 2 --port 43877"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:432 msg=subprocess PATH=/home/nikolas/anaconda3/bin:/home/nikolas/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin OLLAMA_HOST=0.0.0.0:11434 OLLAMA_DEBUG=1 OLLAMA_MAX_LOADED_MODELS=3 OLLAMA_LIBRARY_PATH=/usr/local/lib/ollama:/usr/local/lib/ollama/cuda_v12 LD_LIBRARY_PATH=/usr/local/lib/ollama/cuda_v12:/usr/local/lib/ollama/cuda_v12:/usr/local/lib/ollama:/usr/local/lib/ollama CUDA_VISIBLE_DEVICES=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=sched.go:483 msg="loaded runners" count=1
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server not responding"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.344+03:00 level=INFO source=runner.go:815 msg="starting go runner"
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.344+03:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/local/lib/ollama
Ιουν 23 16:12:57 brainiac ollama[116520]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-alderlake.so
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.349+03:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/local/lib/ollama/cuda_v12
Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: found 1 CUDA devices:
Ιουν 23 16:12:57 brainiac ollama[116520]: Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
Ιουν 23 16:12:57 brainiac ollama[116520]: load_backend: loaded CUDA backend from /usr/local/lib/ollama/cuda_v12/libggml-cuda.so
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.387+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc)
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.387+03:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:43877"
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 4090) - 20180 MiB free
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: loaded meta data with 27 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 (version GGUF V3 (latest))
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 0: general.architecture str = qwen3
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 1: general.type str = model
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B Bf16
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 4: general.size_label str = 8B
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 5: qwen3.block_count u32 = 36
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 4096
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 12288
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 32
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 15: general.file_type u32 = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 16: general.quantization_version u32 = 2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 17: tokenizer.ggml.model str = gpt2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 18: tokenizer.ggml.pre str = qwen2
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,151665] = ["!", """, "#", "$", "%", "&", "'", ...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 20: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 21: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 22: tokenizer.ggml.eos_token_id u32 = 151645
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 151643
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 24: tokenizer.ggml.bos_token_id u32 = 151643
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 25: tokenizer.ggml.add_bos_token bool = false
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 26: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f32: 145 tensors
Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f16: 253 tensors
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file format = GGUF V3 (latest)
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file type = F16
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file size = 14.10 GiB (16.00 BPW)
Ιουν 23 16:12:57 brainiac ollama[116520]: init_tokenizer: initializing tokenizer for type 2
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151660 '<|fim_middle|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151659 '<|fim_prefix|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151653 '<|vision_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151648 '<|box_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151646 '<|object_ref_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151649 '<|box_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151655 '<|image_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151651 '<|quad_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151647 '<|object_ref_end|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151652 '<|vision_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151654 '<|vision_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151656 '<|video_pad|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151644 '<|im_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151661 '<|fim_suffix|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151650 '<|quad_start|>' is not marked as EOG
Ιουν 23 16:12:57 brainiac ollama[116520]: load: special tokens cache size = 22
Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.586+03:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model"
Ιουν 23 16:12:57 brainiac ollama[116520]: load: token to piece cache size = 0.9310 MB
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: arch = qwen3
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab_only = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ctx_train = 40960
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd = 4096
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_layer = 36
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_head = 32
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_head_kv = 8
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_rot = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_swa_pattern = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_head_k = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_head_v = 128
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_gqa = 4
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_k_gqa = 1024
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_v_gqa = 1024
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_norm_eps = 0.0e+00
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_norm_rms_eps = 1.0e-06
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_clamp_kqv = 0.0e+00
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_max_alibi_bias = 0.0e+00
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_logit_scale = 0.0e+00
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_attn_scale = 0.0e+00
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ff = 12288
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_expert = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_expert_used = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: causal attn = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: pooling type = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope type = 2
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope scaling = linear
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: freq_base_train = 1000000.0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: freq_scale_train = 1
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ctx_orig_yarn = 40960
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope_finetuned = unknown
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_conv = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_inner = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_state = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_dt_rank = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_dt_b_c_rms = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model type = 8B
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model params = 7.57 B
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: general.name = Qwen3 Embedding 8B Bf16
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab type = BPE
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_vocab = 151665
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_merges = 151387
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: BOS token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOS token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOT token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: PAD token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: LF token = 198 'Ċ'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM MID token = 151660 '<|fim_middle|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM REP token = 151663 '<|repo_name|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SEP token = 151664 '<|file_sep|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151643 '<|endoftext|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151645 '<|im_end|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151662 '<|fim_pad|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151663 '<|repo_name|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151664 '<|file_sep|>'
Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: max token length = 256
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: loading model tensors, this can take a while... (mmap = true)
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 0 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 1 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 2 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 3 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 4 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 5 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 6 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 7 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 8 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 9 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 10 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 11 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 12 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 13 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 14 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 15 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 16 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 17 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 18 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 19 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 20 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 21 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 22 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 23 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 24 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 25 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 26 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 27 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 28 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 29 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 30 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 31 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 32 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 33 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 34 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 35 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 36 assigned to device CUDA0, is_swa = 0
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: tensor 'token_embd.weight' (f16) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloading 36 repeating layers to GPU
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloading output layer to GPU
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloaded 37/37 layers to GPU
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: CUDA0 model buffer size = 14434.06 MiB
Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: CPU_Mapped model buffer size = 1184.88 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.088+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.20"
Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.339+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.43"
Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.590+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.65"
Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.840+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.88"
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: constructing llama_context
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_seq_max = 2
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx = 8192
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx_per_seq = 4096
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_batch = 1024
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ubatch = 512
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: causal_attn = 1
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: flash_attn = 0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: freq_base = 1000000.0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: freq_scale = 1
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
Ιουν 23 16:12:58 brainiac ollama[116520]: set_abort_callback: call
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA_Host output buffer size = 1.19 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: create_memory: n_ctx = 8192 (padded)
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: kv_size = 8192, type_k = 'f16', type_v = 'f16', n_layer = 36, can_shift = 1, padding = 32
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 0: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 1: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 2: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 3: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 4: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 5: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 6: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 7: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 8: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 9: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 10: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 11: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 12: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 13: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 14: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 15: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 16: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 17: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 18: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 19: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 20: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 21: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 22: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 23: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 24: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 25: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 26: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 27: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 28: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 29: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 30: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 31: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 32: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 33: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 34: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 35: dev = CUDA0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: CUDA0 KV buffer size = 1152.00 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: KV self size = 1152.00 MiB, K (f16): 576.00 MiB, V (f16): 576.00 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: enumerating backends
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: backend_ptrs.size() = 2
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: max_nodes = 65536
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 512, n_seqs = 1
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 1, n_seqs = 1
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 512, n_seqs = 1
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA0 compute buffer size = 560.00 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA_Host compute buffer size = 24.01 MiB
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: graph nodes = 1374
Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: graph splits = 2
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.091+03:00 level=INFO source=server.go:630 msg="llama runner started in 1.76 seconds"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.092+03:00 level=DEBUG source=sched.go:495 msg="finished setting up" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.114+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.128+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=41 used=0 remaining=41
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.222+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=41 prompt=90 used=0 remaining=90
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.248+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=90 prompt=128 used=0 remaining=128
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.275+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=128 prompt=15 used=0 remaining=15
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.296+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=15 prompt=95 used=0 remaining=95
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.322+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=95 prompt=5 used=0 remaining=5
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.342+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=5 prompt=57 used=0 remaining=57
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.365+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=57 prompt=340 used=0 remaining=340
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.405+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=340 prompt=77 used=0 remaining=77
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.405+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.430+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=77 prompt=247 used=0 remaining=247
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.430+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.462+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=247 prompt=252 used=0 remaining=252
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.462+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.494+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=252 prompt=18 used=0 remaining=18
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.494+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.515+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=18 prompt=168 used=0 remaining=168
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.515+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.545+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=168 prompt=143 used=0 remaining=143
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.545+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.573+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=143 prompt=235 used=0 remaining=235
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.573+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.605+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=235 prompt=65 used=0 remaining=65
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.605+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.629+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=65 prompt=86 used=0 remaining=86
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.629+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.655+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=86 prompt=20 used=0 remaining=20
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.655+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.676+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=20 prompt=79 used=0 remaining=79
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.676+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.701+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=79 prompt=197 used=0 remaining=197
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.701+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.733+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=197 prompt=124 used=0 remaining=124
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.733+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.759+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=124 prompt=136 used=0 remaining=136
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.759+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.790+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=136 prompt=101 used=0 remaining=101
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.790+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.815+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=101 prompt=36 used=0 remaining=36
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.815+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.837+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=36 prompt=206 used=0 remaining=206
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.837+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.869+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=206 prompt=307 used=0 remaining=307
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.869+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.908+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=307 prompt=14 used=0 remaining=14
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.908+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.929+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=14 prompt=87 used=0 remaining=87
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.929+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.954+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=87 prompt=125 used=0 remaining=125
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.954+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
Ιουν 23 16:12:59 brainiac ollama[116520]: [GIN] 2025/06/23 - 16:12:59 | 500 | 3.075249638s | 10.0.20.178 | POST "/api/embed"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:503 msg="context for request finished"
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:343 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192 duration=5m0s
Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:361 msg="after processing request finished event" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192 refCount=0

`

<!-- gh-comment-id:2996467327 --> @NikolasTh90 commented on GitHub (Jun 23, 2025): I am leaving my debug trace `Ιουν 23 16:12:49 brainiac ollama[116520]: CUDA driver version: 12.4 Ιουν 23 16:12:49 brainiac ollama[116520]: calling cuDeviceGetCount Ιουν 23 16:12:49 brainiac ollama[116520]: device count 1 Ιουν 23 16:12:49 brainiac ollama[116520]: time=2025-06-23T16:12:49.946+03:00 level=DEBUG source=gpu.go:125 msg="detected GPUs" count=1 library=/usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01 Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] CUDA totalMem 23995mb Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] CUDA freeMem 20180mb Ιουν 23 16:12:50 brainiac ollama[116520]: [GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01] Compute Capability 8.9 Ιουν 23 16:12:50 brainiac ollama[116520]: time=2025-06-23T16:12:50.194+03:00 level=DEBUG source=amd_linux.go:419 msg="amdgpu driver not detected /sys/module/amdgpu" Ιουν 23 16:12:50 brainiac ollama[116520]: releasing cuda driver library Ιουν 23 16:12:50 brainiac ollama[116520]: time=2025-06-23T16:12:50.194+03:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 library=cuda variant=v12 compute=8.9 driver=12.4 name="NVIDIA GeForce RTX 4090" total="23.4 GiB" available="19.7 GiB" Ιουν 23 16:12:56 brainiac ollama[116520]: time=2025-06-23T16:12:56.932+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 Ιουν 23 16:12:56 brainiac ollama[116520]: time=2025-06-23T16:12:56.932+03:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="188.5 GiB" before.free="181.1 GiB" before.free_swap="2.0 GiB" now.total="188.5 GiB" now.free="181.0 GiB" now.free_swap="2.0 GiB" Ιουν 23 16:12:56 brainiac ollama[116520]: initializing /usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuInit - 0x7cff1267ce20 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDriverGetVersion - 0x7cff1267ce40 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetCount - 0x7cff1267ce80 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGet - 0x7cff1267ce60 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetAttribute - 0x7cff1267cf60 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetUuid - 0x7cff1267cec0 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuDeviceGetName - 0x7cff1267cea0 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuCtxCreate_v3 - 0x7cff1267d140 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuMemGetInfo_v2 - 0x7cff12687080 Ιουν 23 16:12:56 brainiac ollama[116520]: dlsym: cuCtxDestroy - 0x7cff126e19c0 Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuInit Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuDriverGetVersion Ιουν 23 16:12:56 brainiac ollama[116520]: raw version 0x2f08 Ιουν 23 16:12:56 brainiac ollama[116520]: CUDA driver version: 12.4 Ιουν 23 16:12:56 brainiac ollama[116520]: calling cuDeviceGetCount Ιουν 23 16:12:56 brainiac ollama[116520]: device count 1 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.070+03:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 name="NVIDIA GeForce RTX 4090" overhead="0 B" before.total="23.4 GiB" before.free="19.7 GiB" now.total="23.4 GiB" now.free="19.7 GiB" now.used="3.7 GiB" Ιουν 23 16:12:57 brainiac ollama[116520]: releasing cuda driver library Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.070+03:00 level=DEBUG source=sched.go:185 msg="updating default concurrency" OLLAMA_MAX_LOADED_MODELS=3 gpu_count=1 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.077+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=sched.go:228 msg="loading first model" model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.084+03:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[19.7 GiB]" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3.vision.block_count default=0 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 parallel=2 available=21160460288 required="16.8 GiB" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.085+03:00 level=DEBUG source=gpu.go:391 msg="updating system memory data" before.total="188.5 GiB" before.free="181.0 GiB" before.free_swap="2.0 GiB" now.total="188.5 GiB" now.free="181.0 GiB" now.free_swap="2.0 GiB" Ιουν 23 16:12:57 brainiac ollama[116520]: initializing /usr/lib/x86_64-linux-gnu/libcuda.so.550.163.01 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuInit - 0x7cff1267ce20 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDriverGetVersion - 0x7cff1267ce40 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetCount - 0x7cff1267ce80 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGet - 0x7cff1267ce60 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetAttribute - 0x7cff1267cf60 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetUuid - 0x7cff1267cec0 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuDeviceGetName - 0x7cff1267cea0 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuCtxCreate_v3 - 0x7cff1267d140 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuMemGetInfo_v2 - 0x7cff12687080 Ιουν 23 16:12:57 brainiac ollama[116520]: dlsym: cuCtxDestroy - 0x7cff126e19c0 Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuInit Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuDriverGetVersion Ιουν 23 16:12:57 brainiac ollama[116520]: raw version 0x2f08 Ιουν 23 16:12:57 brainiac ollama[116520]: CUDA driver version: 12.4 Ιουν 23 16:12:57 brainiac ollama[116520]: calling cuDeviceGetCount Ιουν 23 16:12:57 brainiac ollama[116520]: device count 1 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=gpu.go:441 msg="updating cuda memory data" gpu=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 name="NVIDIA GeForce RTX 4090" overhead="0 B" before.total="23.4 GiB" before.free="19.7 GiB" now.total="23.4 GiB" now.free="19.7 GiB" now.used="3.7 GiB" Ιουν 23 16:12:57 brainiac ollama[116520]: releasing cuda driver library Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=INFO source=server.go:135 msg="system memory" total="188.5 GiB" free="181.0 GiB" free_swap="2.0 GiB" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=memory.go:111 msg=evaluating library=cuda gpu_count=1 available="[19.7 GiB]" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=qwen3.vision.block_count default=0 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=INFO source=server.go:168 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[19.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="16.8 GiB" memory.required.partial="16.8 GiB" memory.required.kv="1.1 GiB" memory.required.allocations="[16.8 GiB]" memory.weights.total="14.1 GiB" memory.weights.repeating="12.9 GiB" memory.weights.nonrepeating="1.2 GiB" memory.graph.full="768.0 MiB" memory.graph.partial="768.0 MiB" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.219+03:00 level=DEBUG source=server.go:284 msg="compatible gpu libraries" compatible="[cuda_v12 cuda_v11]" Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: loaded meta data with 27 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 (version GGUF V3 (latest)) Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 0: general.architecture str = qwen3 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 1: general.type str = model Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B Bf16 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 4: general.size_label str = 8B Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 5: qwen3.block_count u32 = 36 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 4096 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 12288 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 32 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 15: general.file_type u32 = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 16: general.quantization_version u32 = 2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 17: tokenizer.ggml.model str = gpt2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 18: tokenizer.ggml.pre str = qwen2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,151665] = ["!", "\"", "#", "$", "%", "&", "'", ... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 20: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 21: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 22: tokenizer.ggml.eos_token_id u32 = 151645 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 151643 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 24: tokenizer.ggml.bos_token_id u32 = 151643 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 25: tokenizer.ggml.add_bos_token bool = false Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 26: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f32: 145 tensors Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f16: 253 tensors Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file format = GGUF V3 (latest) Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file type = F16 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file size = 14.10 GiB (16.00 BPW) Ιουν 23 16:12:57 brainiac ollama[116520]: init_tokenizer: initializing tokenizer for type 2 Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151660 '<|fim_middle|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151659 '<|fim_prefix|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151653 '<|vision_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151648 '<|box_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151646 '<|object_ref_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151649 '<|box_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151655 '<|image_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151651 '<|quad_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151647 '<|object_ref_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151652 '<|vision_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151654 '<|vision_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151656 '<|video_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151644 '<|im_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151661 '<|fim_suffix|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151650 '<|quad_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: special tokens cache size = 22 Ιουν 23 16:12:57 brainiac ollama[116520]: load: token to piece cache size = 0.9310 MB Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: arch = qwen3 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab_only = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model type = ?B Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model params = 7.57 B Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: general.name = Qwen3 Embedding 8B Bf16 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab type = BPE Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_vocab = 151665 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_merges = 151387 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: BOS token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOS token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOT token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: PAD token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: LF token = 198 'Ċ' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PRE token = 151659 '<|fim_prefix|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SUF token = 151661 '<|fim_suffix|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM MID token = 151660 '<|fim_middle|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PAD token = 151662 '<|fim_pad|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM REP token = 151663 '<|repo_name|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SEP token = 151664 '<|file_sep|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151662 '<|fim_pad|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151663 '<|repo_name|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151664 '<|file_sep|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: max token length = 256 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_load: vocab only - skipping tensors Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:360 msg="adding gpu library" path=/usr/local/lib/ollama/cuda_v12 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:367 msg="adding gpu dependency paths" paths=[/usr/local/lib/ollama/cuda_v12] Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:431 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 --ctx-size 8192 --batch-size 512 --n-gpu-layers 37 --threads 8 --parallel 2 --port 43877" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=DEBUG source=server.go:432 msg=subprocess PATH=/home/nikolas/anaconda3/bin:/home/nikolas/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin OLLAMA_HOST=0.0.0.0:11434 OLLAMA_DEBUG=1 OLLAMA_MAX_LOADED_MODELS=3 OLLAMA_LIBRARY_PATH=/usr/local/lib/ollama:/usr/local/lib/ollama/cuda_v12 LD_LIBRARY_PATH=/usr/local/lib/ollama/cuda_v12:/usr/local/lib/ollama/cuda_v12:/usr/local/lib/ollama:/usr/local/lib/ollama CUDA_VISIBLE_DEVICES=GPU-dfea5d8a-bc26-58e4-88af-51bdaf629a01 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=sched.go:483 msg="loaded runners" count=1 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:591 msg="waiting for llama runner to start responding" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.335+03:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server not responding" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.344+03:00 level=INFO source=runner.go:815 msg="starting go runner" Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.344+03:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/local/lib/ollama Ιουν 23 16:12:57 brainiac ollama[116520]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-alderlake.so Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.349+03:00 level=DEBUG source=ggml.go:94 msg="ggml backend load all from path" path=/usr/local/lib/ollama/cuda_v12 Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no Ιουν 23 16:12:57 brainiac ollama[116520]: ggml_cuda_init: found 1 CUDA devices: Ιουν 23 16:12:57 brainiac ollama[116520]: Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes Ιουν 23 16:12:57 brainiac ollama[116520]: load_backend: loaded CUDA backend from /usr/local/lib/ollama/cuda_v12/libggml-cuda.so Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.387+03:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX_VNNI=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc) Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.387+03:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:43877" Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 4090) - 20180 MiB free Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: loaded meta data with 27 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 (version GGUF V3 (latest)) Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 0: general.architecture str = qwen3 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 1: general.type str = model Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B Bf16 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 4: general.size_label str = 8B Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 5: qwen3.block_count u32 = 36 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 6: qwen3.context_length u32 = 40960 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 7: qwen3.embedding_length u32 = 4096 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 8: qwen3.feed_forward_length u32 = 12288 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 9: qwen3.attention.head_count u32 = 32 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 10: qwen3.attention.head_count_kv u32 = 8 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 11: qwen3.rope.freq_base f32 = 1000000.000000 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 12: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 13: qwen3.attention.key_length u32 = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 14: qwen3.attention.value_length u32 = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 15: general.file_type u32 = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 16: general.quantization_version u32 = 2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 17: tokenizer.ggml.model str = gpt2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 18: tokenizer.ggml.pre str = qwen2 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,151665] = ["!", "\"", "#", "$", "%", "&", "'", ... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 20: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 21: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 22: tokenizer.ggml.eos_token_id u32 = 151645 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 151643 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 24: tokenizer.ggml.bos_token_id u32 = 151643 Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 25: tokenizer.ggml.add_bos_token bool = false Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - kv 26: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f32: 145 tensors Ιουν 23 16:12:57 brainiac ollama[116520]: llama_model_loader: - type f16: 253 tensors Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file format = GGUF V3 (latest) Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file type = F16 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: file size = 14.10 GiB (16.00 BPW) Ιουν 23 16:12:57 brainiac ollama[116520]: init_tokenizer: initializing tokenizer for type 2 Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151660 '<|fim_middle|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151659 '<|fim_prefix|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151653 '<|vision_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151648 '<|box_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151646 '<|object_ref_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151649 '<|box_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151655 '<|image_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151651 '<|quad_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151647 '<|object_ref_end|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151652 '<|vision_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151654 '<|vision_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151656 '<|video_pad|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151644 '<|im_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151661 '<|fim_suffix|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: control token: 151650 '<|quad_start|>' is not marked as EOG Ιουν 23 16:12:57 brainiac ollama[116520]: load: special tokens cache size = 22 Ιουν 23 16:12:57 brainiac ollama[116520]: time=2025-06-23T16:12:57.586+03:00 level=INFO source=server.go:625 msg="waiting for server to become available" status="llm server loading model" Ιουν 23 16:12:57 brainiac ollama[116520]: load: token to piece cache size = 0.9310 MB Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: arch = qwen3 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab_only = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ctx_train = 40960 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd = 4096 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_layer = 36 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_head = 32 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_head_kv = 8 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_rot = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_swa_pattern = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_head_k = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_head_v = 128 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_gqa = 4 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_k_gqa = 1024 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_embd_v_gqa = 1024 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_norm_eps = 0.0e+00 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_norm_rms_eps = 1.0e-06 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_clamp_kqv = 0.0e+00 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_max_alibi_bias = 0.0e+00 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_logit_scale = 0.0e+00 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: f_attn_scale = 0.0e+00 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ff = 12288 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_expert = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_expert_used = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: causal attn = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: pooling type = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope type = 2 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope scaling = linear Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: freq_base_train = 1000000.0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: freq_scale_train = 1 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_ctx_orig_yarn = 40960 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: rope_finetuned = unknown Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_conv = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_inner = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_d_state = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_dt_rank = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: ssm_dt_b_c_rms = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model type = 8B Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: model params = 7.57 B Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: general.name = Qwen3 Embedding 8B Bf16 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: vocab type = BPE Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_vocab = 151665 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: n_merges = 151387 Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: BOS token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOS token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOT token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: PAD token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: LF token = 198 'Ċ' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PRE token = 151659 '<|fim_prefix|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SUF token = 151661 '<|fim_suffix|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM MID token = 151660 '<|fim_middle|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM PAD token = 151662 '<|fim_pad|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM REP token = 151663 '<|repo_name|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: FIM SEP token = 151664 '<|file_sep|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151643 '<|endoftext|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151645 '<|im_end|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151662 '<|fim_pad|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151663 '<|repo_name|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: EOG token = 151664 '<|file_sep|>' Ιουν 23 16:12:57 brainiac ollama[116520]: print_info: max token length = 256 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: loading model tensors, this can take a while... (mmap = true) Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 0 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 1 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 2 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 3 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 4 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 5 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 6 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 7 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 8 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 9 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 10 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 11 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 12 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 13 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 14 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 15 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 16 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 17 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 18 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 19 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 20 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 21 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 22 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 23 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 24 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 25 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 26 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 27 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 28 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 29 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 30 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 31 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 32 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 33 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 34 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 35 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: layer 36 assigned to device CUDA0, is_swa = 0 Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: tensor 'token_embd.weight' (f16) (and 0 others) cannot be used with preferred buffer type CUDA_Host, using CPU instead Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloading 36 repeating layers to GPU Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloading output layer to GPU Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: offloaded 37/37 layers to GPU Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: CUDA0 model buffer size = 14434.06 MiB Ιουν 23 16:12:57 brainiac ollama[116520]: load_tensors: CPU_Mapped model buffer size = 1184.88 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.088+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.20" Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.339+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.43" Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.590+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.65" Ιουν 23 16:12:58 brainiac ollama[116520]: time=2025-06-23T16:12:58.840+03:00 level=DEBUG source=server.go:636 msg="model load progress 0.88" Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: constructing llama_context Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_seq_max = 2 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx = 8192 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx_per_seq = 4096 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_batch = 1024 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ubatch = 512 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: causal_attn = 1 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: flash_attn = 0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: freq_base = 1000000.0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: freq_scale = 1 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized Ιουν 23 16:12:58 brainiac ollama[116520]: set_abort_callback: call Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA_Host output buffer size = 1.19 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: create_memory: n_ctx = 8192 (padded) Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: kv_size = 8192, type_k = 'f16', type_v = 'f16', n_layer = 36, can_shift = 1, padding = 32 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 0: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 1: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 2: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 3: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 4: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 5: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 6: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 7: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 8: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 9: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 10: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 11: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 12: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 13: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 14: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 15: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 16: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 17: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 18: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 19: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 20: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 21: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 22: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 23: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 24: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 25: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 26: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 27: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 28: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 29: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 30: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 31: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 32: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 33: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 34: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: layer 35: dev = CUDA0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: CUDA0 KV buffer size = 1152.00 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: llama_kv_cache_unified: KV self size = 1152.00 MiB, K (f16): 576.00 MiB, V (f16): 576.00 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: enumerating backends Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: backend_ptrs.size() = 2 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: max_nodes = 65536 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 512, n_seqs = 1 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 1, n_seqs = 1 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: reserving graph for n_tokens = 512, n_seqs = 1 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA0 compute buffer size = 560.00 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: CUDA_Host compute buffer size = 24.01 MiB Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: graph nodes = 1374 Ιουν 23 16:12:58 brainiac ollama[116520]: llama_context: graph splits = 2 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.091+03:00 level=INFO source=server.go:630 msg="llama runner started in 1.76 seconds" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.092+03:00 level=DEBUG source=sched.go:495 msg="finished setting up" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.114+03:00 level=DEBUG source=ggml.go:155 msg="key not found" key=general.alignment default=32 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.128+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=0 prompt=41 used=0 remaining=41 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.222+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=41 prompt=90 used=0 remaining=90 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.248+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=90 prompt=128 used=0 remaining=128 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.275+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=128 prompt=15 used=0 remaining=15 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.296+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=15 prompt=95 used=0 remaining=95 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.322+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=95 prompt=5 used=0 remaining=5 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.342+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=5 prompt=57 used=0 remaining=57 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.365+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=57 prompt=340 used=0 remaining=340 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.405+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=340 prompt=77 used=0 remaining=77 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.405+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.430+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=77 prompt=247 used=0 remaining=247 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.430+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.462+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=247 prompt=252 used=0 remaining=252 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.462+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.494+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=252 prompt=18 used=0 remaining=18 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.494+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.515+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=18 prompt=168 used=0 remaining=168 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.515+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.545+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=168 prompt=143 used=0 remaining=143 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.545+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.573+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=143 prompt=235 used=0 remaining=235 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.573+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.605+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=235 prompt=65 used=0 remaining=65 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.605+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.629+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=65 prompt=86 used=0 remaining=86 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.629+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.655+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=86 prompt=20 used=0 remaining=20 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.655+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.676+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=20 prompt=79 used=0 remaining=79 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.676+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.701+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=79 prompt=197 used=0 remaining=197 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.701+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.733+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=197 prompt=124 used=0 remaining=124 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.733+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.759+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=124 prompt=136 used=0 remaining=136 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.759+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.790+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=136 prompt=101 used=0 remaining=101 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.790+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.815+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=101 prompt=36 used=0 remaining=36 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.815+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.837+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=36 prompt=206 used=0 remaining=206 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.837+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.869+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=206 prompt=307 used=0 remaining=307 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.869+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.908+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=307 prompt=14 used=0 remaining=14 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.908+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.929+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=14 prompt=87 used=0 remaining=87 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.929+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.954+03:00 level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=87 prompt=125 used=0 remaining=125 Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.954+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=INFO source=server.go:939 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" Ιουν 23 16:12:59 brainiac ollama[116520]: [GIN] 2025/06/23 - 16:12:59 | 500 | 3.075249638s | 10.0.20.178 | POST "/api/embed" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:503 msg="context for request finished" Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:343 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192 duration=5m0s Ιουν 23 16:12:59 brainiac ollama[116520]: time=2025-06-23T16:12:59.981+03:00 level=DEBUG source=sched.go:361 msg="after processing request finished event" runner.name=registry.ollama.ai/dengcao/Qwen3-Embedding-8B:F16 runner.inference=cuda runner.devices=1 runner.size="16.8 GiB" runner.vram="16.8 GiB" runner.parallel=2 runner.pid=117746 runner.model=/usr/share/ollama/.ollama/models/blobs/sha256-01e070a939333b2a610ff7407ba016be0def3f804edce8958b879c8012e8f055 runner.num_ctx=8192 refCount=0 `

GiteaMirror commented 2026-04-12 17:43:46 -05:00

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@linabellbiu commented on GitHub (Jul 23, 2025):

I encountered the same problem.

(base) coke@coke:~/dify/docker$ journalctl -u ollama -f
7月 23 11:12:24 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:24 | 200 | 424.434928ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 441.649524ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 418.534893ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 397.615549ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:25 coke ollama[52538]: time=2025-07-23T11:12:25.802+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 500 | 496.054ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 200 | 521.802417ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 200 | 353.466301ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:12:26 coke ollama[52538]: time=2025-07-23T11:12:26.895+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 500 | 452.757032ms | 172.19.0.8 | POST "/api/embed"

7月 23 11:22:41 coke ollama[52538]: time=2025-07-23T11:22:41.980+08:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 gpu=GPU-6c63cf01-9a2d-4ccc-fbdd-e474b84adaae parallel=1 available=16599744512 required="5.9 GiB"
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.612+08:00 level=INFO source=server.go:135 msg="system memory" total="125.6 GiB" free="120.0 GiB" free_swap="8.0 GiB"
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.612+08:00 level=INFO source=server.go:175 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[15.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.9 GiB" memory.required.partial="5.9 GiB" memory.required.kv="576.0 MiB" memory.required.allocations="[5.9 GiB]" memory.weights.total="4.4 GiB" memory.weights.repeating="3.9 GiB" memory.weights.nonrepeating="486.0 MiB" memory.graph.full="384.0 MiB" memory.graph.partial="384.0 MiB"
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: loaded meta data with 36 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 (version GGUF V3 (latest))
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 0: general.architecture str = qwen3
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 1: general.type str = model
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 4: general.size_label str = 8B
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 5: general.license str = apache-2.0
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 6: general.base_model.count u32 = 1
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 7: general.base_model.0.name str = Qwen3 8B Base
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 8: general.base_model.0.organization str = Qwen
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 9: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3-8B-...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 10: general.tags arr[str,5] = ["transformers", "sentence-transforme...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 11: qwen3.block_count u32 = 36
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 12: qwen3.context_length u32 = 40960
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 13: qwen3.embedding_length u32 = 4096
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 14: qwen3.feed_forward_length u32 = 12288
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 15: qwen3.attention.head_count u32 = 32
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 16: qwen3.attention.head_count_kv u32 = 8
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 17: qwen3.rope.freq_base f32 = 1000000.000000
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 18: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 19: qwen3.attention.key_length u32 = 128
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 20: qwen3.attention.value_length u32 = 128
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 21: qwen3.pooling_type u32 = 3
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 23: tokenizer.ggml.pre str = qwen2
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,151665] = ["!", """, "#", "$", "%", "&", "'", ...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 151643
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 28: tokenizer.ggml.padding_token_id u32 = 151643
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 29: tokenizer.ggml.eot_token_id u32 = 151645
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 31: tokenizer.ggml.add_eos_token bool = true
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 32: tokenizer.ggml.add_bos_token bool = false
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 33: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 34: general.quantization_version u32 = 2
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 35: general.file_type u32 = 15
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type f32: 145 tensors
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type q4_K: 216 tensors
7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type q6_K: 37 tensors
7月 23 11:22:42 coke ollama[52538]: print_info: file format = GGUF V3 (latest)
7月 23 11:22:42 coke ollama[52538]: print_info: file type = Q4_K - Medium
7月 23 11:22:42 coke ollama[52538]: print_info: file size = 4.35 GiB (4.94 BPW)
7月 23 11:22:42 coke ollama[52538]: load: special tokens cache size = 22
7月 23 11:22:42 coke ollama[52538]: load: token to piece cache size = 0.9310 MB
7月 23 11:22:42 coke ollama[52538]: print_info: arch = qwen3
7月 23 11:22:42 coke ollama[52538]: print_info: vocab_only = 1
7月 23 11:22:42 coke ollama[52538]: print_info: model type = ?B
7月 23 11:22:42 coke ollama[52538]: print_info: model params = 7.57 B
7月 23 11:22:42 coke ollama[52538]: print_info: general.name = Qwen3 Embedding 8B
7月 23 11:22:42 coke ollama[52538]: print_info: vocab type = BPE
7月 23 11:22:42 coke ollama[52538]: print_info: n_vocab = 151665
7月 23 11:22:42 coke ollama[52538]: print_info: n_merges = 151387
7月 23 11:22:42 coke ollama[52538]: print_info: BOS token = 151643 '<|endoftext|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOS token = 151643 '<|endoftext|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOT token = 151645 '<|im_end|>'
7月 23 11:22:42 coke ollama[52538]: print_info: PAD token = 151643 '<|endoftext|>'
7月 23 11:22:42 coke ollama[52538]: print_info: LF token = 198 'Ċ'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM MID token = 151660 '<|fim_middle|>'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM REP token = 151663 '<|repo_name|>'
7月 23 11:22:42 coke ollama[52538]: print_info: FIM SEP token = 151664 '<|file_sep|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151643 '<|endoftext|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151645 '<|im_end|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151662 '<|fim_pad|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151663 '<|repo_name|>'
7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151664 '<|file_sep|>'
7月 23 11:22:42 coke ollama[52538]: print_info: max token length = 256
7月 23 11:22:42 coke ollama[52538]: llama_model_load: vocab only - skipping tensors
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.911+08:00 level=INFO source=server.go:438 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 --ctx-size 4096 --batch-size 512 --n-gpu-layers 37 --threads 36 --parallel 1 --port 39047"
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=sched.go:483 msg="loaded runners" count=1
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=server.go:598 msg="waiting for llama runner to start responding"
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding"
7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.933+08:00 level=INFO source=runner.go:815 msg="starting go runner"
7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: found 1 CUDA devices:
7月 23 11:22:43 coke ollama[52538]: Device 0: Tesla V100-SXM2-16GB, compute capability 7.0, VMM: yes
7月 23 11:22:43 coke ollama[52538]: load_backend: loaded CUDA backend from /usr/local/lib/ollama/libggml-cuda.so
7月 23 11:22:43 coke ollama[52538]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-haswell.so
7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.044+08:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc)
7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.045+08:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:39047"
7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.164+08:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model"
7月 23 11:22:43 coke ollama[52538]: llama_model_load_from_file_impl: using device CUDA0 (Tesla V100-SXM2-16GB) - 15830 MiB free
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: loaded meta data with 36 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 (version GGUF V3 (latest))
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 0: general.architecture str = qwen3
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 1: general.type str = model
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 4: general.size_label str = 8B
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 5: general.license str = apache-2.0
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 6: general.base_model.count u32 = 1
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 7: general.base_model.0.name str = Qwen3 8B Base
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 8: general.base_model.0.organization str = Qwen
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 9: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3-8B-...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 10: general.tags arr[str,5] = ["transformers", "sentence-transforme...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 11: qwen3.block_count u32 = 36
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 12: qwen3.context_length u32 = 40960
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 13: qwen3.embedding_length u32 = 4096
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 14: qwen3.feed_forward_length u32 = 12288
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 15: qwen3.attention.head_count u32 = 32
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 16: qwen3.attention.head_count_kv u32 = 8
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 17: qwen3.rope.freq_base f32 = 1000000.000000
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 18: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 19: qwen3.attention.key_length u32 = 128
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 20: qwen3.attention.value_length u32 = 128
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 21: qwen3.pooling_type u32 = 3
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 23: tokenizer.ggml.pre str = qwen2
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,151665] = ["!", """, "#", "$", "%", "&", "'", ...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 151643
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 28: tokenizer.ggml.padding_token_id u32 = 151643
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 29: tokenizer.ggml.eot_token_id u32 = 151645
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 31: tokenizer.ggml.add_eos_token bool = true
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 32: tokenizer.ggml.add_bos_token bool = false
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 33: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 34: general.quantization_version u32 = 2
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 35: general.file_type u32 = 15
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type f32: 145 tensors
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type q4_K: 216 tensors
7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type q6_K: 37 tensors
7月 23 11:22:43 coke ollama[52538]: print_info: file format = GGUF V3 (latest)
7月 23 11:22:43 coke ollama[52538]: print_info: file type = Q4_K - Medium
7月 23 11:22:43 coke ollama[52538]: print_info: file size = 4.35 GiB (4.94 BPW)
7月 23 11:22:43 coke ollama[52538]: load: special tokens cache size = 22
7月 23 11:22:43 coke ollama[52538]: load: token to piece cache size = 0.9310 MB
7月 23 11:22:43 coke ollama[52538]: print_info: arch = qwen3
7月 23 11:22:43 coke ollama[52538]: print_info: vocab_only = 0
7月 23 11:22:43 coke ollama[52538]: print_info: n_ctx_train = 40960
7月 23 11:22:43 coke ollama[52538]: print_info: n_embd = 4096
7月 23 11:22:43 coke ollama[52538]: print_info: n_layer = 36
7月 23 11:22:43 coke ollama[52538]: print_info: n_head = 32
7月 23 11:22:43 coke ollama[52538]: print_info: n_head_kv = 8
7月 23 11:22:43 coke ollama[52538]: print_info: n_rot = 128
7月 23 11:22:43 coke ollama[52538]: print_info: n_swa = 0
7月 23 11:22:43 coke ollama[52538]: print_info: n_swa_pattern = 1
7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_head_k = 128
7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_head_v = 128
7月 23 11:22:43 coke ollama[52538]: print_info: n_gqa = 4
7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_k_gqa = 1024
7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_v_gqa = 1024
7月 23 11:22:43 coke ollama[52538]: print_info: f_norm_eps = 0.0e+00
7月 23 11:22:43 coke ollama[52538]: print_info: f_norm_rms_eps = 1.0e-06
7月 23 11:22:43 coke ollama[52538]: print_info: f_clamp_kqv = 0.0e+00
7月 23 11:22:43 coke ollama[52538]: print_info: f_max_alibi_bias = 0.0e+00
7月 23 11:22:43 coke ollama[52538]: print_info: f_logit_scale = 0.0e+00
7月 23 11:22:43 coke ollama[52538]: print_info: f_attn_scale = 0.0e+00
7月 23 11:22:43 coke ollama[52538]: print_info: n_ff = 12288
7月 23 11:22:43 coke ollama[52538]: print_info: n_expert = 0
7月 23 11:22:43 coke ollama[52538]: print_info: n_expert_used = 0
7月 23 11:22:43 coke ollama[52538]: print_info: causal attn = 1
7月 23 11:22:43 coke ollama[52538]: print_info: pooling type = 0
7月 23 11:22:43 coke ollama[52538]: print_info: rope type = 2
7月 23 11:22:43 coke ollama[52538]: print_info: rope scaling = linear
7月 23 11:22:43 coke ollama[52538]: print_info: freq_base_train = 1000000.0
7月 23 11:22:43 coke ollama[52538]: print_info: freq_scale_train = 1
7月 23 11:22:43 coke ollama[52538]: print_info: n_ctx_orig_yarn = 40960
7月 23 11:22:43 coke ollama[52538]: print_info: rope_finetuned = unknown
7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_conv = 0
7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_inner = 0
7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_state = 0
7月 23 11:22:43 coke ollama[52538]: print_info: ssm_dt_rank = 0
7月 23 11:22:43 coke ollama[52538]: print_info: ssm_dt_b_c_rms = 0
7月 23 11:22:43 coke ollama[52538]: print_info: model type = 8B
7月 23 11:22:43 coke ollama[52538]: print_info: model params = 7.57 B
7月 23 11:22:43 coke ollama[52538]: print_info: general.name = Qwen3 Embedding 8B
7月 23 11:22:43 coke ollama[52538]: print_info: vocab type = BPE
7月 23 11:22:43 coke ollama[52538]: print_info: n_vocab = 151665
7月 23 11:22:43 coke ollama[52538]: print_info: n_merges = 151387
7月 23 11:22:43 coke ollama[52538]: print_info: BOS token = 151643 '<|endoftext|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOS token = 151643 '<|endoftext|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOT token = 151645 '<|im_end|>'
7月 23 11:22:43 coke ollama[52538]: print_info: PAD token = 151643 '<|endoftext|>'
7月 23 11:22:43 coke ollama[52538]: print_info: LF token = 198 'Ċ'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM PRE token = 151659 '<|fim_prefix|>'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM SUF token = 151661 '<|fim_suffix|>'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM MID token = 151660 '<|fim_middle|>'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM PAD token = 151662 '<|fim_pad|>'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM REP token = 151663 '<|repo_name|>'
7月 23 11:22:43 coke ollama[52538]: print_info: FIM SEP token = 151664 '<|file_sep|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151643 '<|endoftext|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151645 '<|im_end|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151662 '<|fim_pad|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151663 '<|repo_name|>'
7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151664 '<|file_sep|>'
7月 23 11:22:43 coke ollama[52538]: print_info: max token length = 256
7月 23 11:22:43 coke ollama[52538]: load_tensors: loading model tensors, this can take a while... (mmap = true)
7月 23 11:22:43 coke ollama[52538]: load_tensors: offloading 36 repeating layers to GPU
7月 23 11:22:43 coke ollama[52538]: load_tensors: offloading output layer to GPU
7月 23 11:22:43 coke ollama[52538]: load_tensors: offloaded 37/37 layers to GPU
7月 23 11:22:43 coke ollama[52538]: load_tensors: CUDA0 model buffer size = 4454.48 MiB
7月 23 11:22:43 coke ollama[52538]: load_tensors: CPU_Mapped model buffer size = 485.99 MiB
7月 23 11:22:44 coke ollama[52538]: llama_context: constructing llama_context
7月 23 11:22:44 coke ollama[52538]: llama_context: n_seq_max = 1
7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx = 4096
7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx_per_seq = 4096
7月 23 11:22:44 coke ollama[52538]: llama_context: n_batch = 512
7月 23 11:22:44 coke ollama[52538]: llama_context: n_ubatch = 512
7月 23 11:22:44 coke ollama[52538]: llama_context: causal_attn = 1
7月 23 11:22:44 coke ollama[52538]: llama_context: flash_attn = 0
7月 23 11:22:44 coke ollama[52538]: llama_context: freq_base = 1000000.0
7月 23 11:22:44 coke ollama[52538]: llama_context: freq_scale = 1
7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA_Host output buffer size = 0.59 MiB
7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: kv_size = 4096, type_k = 'f16', type_v = 'f16', n_layer = 36, can_shift = 1, padding = 32
7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: CUDA0 KV buffer size = 576.00 MiB
7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: KV self size = 576.00 MiB, K (f16): 288.00 MiB, V (f16): 288.00 MiB
7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA0 compute buffer size = 304.22 MiB
7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA_Host compute buffer size = 16.01 MiB
7月 23 11:22:44 coke ollama[52538]: llama_context: graph nodes = 1374
7月 23 11:22:44 coke ollama[52538]: llama_context: graph splits = 2
7月 23 11:22:44 coke ollama[52538]: time=2025-07-23T11:22:44.672+08:00 level=INFO source=server.go:637 msg="llama runner started in 1.76 seconds"
7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 3.95730585s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.097434459s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.307573308s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.669465537s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.804644006s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 4.904773446s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.134000884s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.228851286s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.341684237s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.400859549s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 1.689496291s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 1.678098205s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.686379843s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.538931326s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.724966529s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.917776609s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 1.956736046s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.012959536s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.188382936s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.246491936s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.135688918s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.120466654s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.121280637s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.061815222s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.023892558s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 1.85088303s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.8030479s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.987750466s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.946864034s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.931853169s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 2.015723593s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.989309472s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.922490633s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 2.0567454s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.868851876s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.967369102s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 2.014157439s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.678476458s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.818347551s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.827386364s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.958683725s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 1.964767401s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.147872275s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.002911678s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.106361414s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.020523508s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.986329621s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 2.157722921s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 2.056154139s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.898146904s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.750018525s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.792368105s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.682409342s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.729942534s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.718403339s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.806173898s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.835032129s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 1.956552307s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 1.838304157s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 2.117775535s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 2.065336634s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.059879619s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.182850753s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.242307876s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.057612019s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.050148604s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.066062286s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.05169877s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.259331386s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.146808913s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.157495167s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.169183221s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.045220267s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.08916033s | 172.19.0.8 | POST "/api/embed"
7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.271678594s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.242806503s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.206771551s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.112279391s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 1.972523275s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 1.966753362s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 1.968742495s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.111598758s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.118126409s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.12256577s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.137052163s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 1.977210664s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.129386198s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.104305861s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.25898748s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.22796644s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.377335482s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.229183565s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.144004666s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.045762367s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.096489163s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.397861259s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.294938882s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.270212051s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.093897672s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.133588129s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 1.89427208s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.020326876s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.108986163s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 2.15937526s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 2.10358666s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 1.954297774s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 1.918591215s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.067281978s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.079225175s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 1.906419489s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.09282623s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.037115116s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 1.929813435s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 1.904462873s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 1.920355956s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 2.026594488s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 2.182131606s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.057251869s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.084850578s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.377947553s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.375754502s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 200 | 2.386479444s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 200 | 2.4657119s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.549+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.471647682s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.761+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.451126228s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.929+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.297690143s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.201706198s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.353981302s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.377790703s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.177294558s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.189870298s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.099538443s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.103157126s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 1.520879897s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 1.312047266s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 200 | 1.325906987s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:13 coke ollama[52538]: time=2025-07-23T11:23:13.390+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 500 | 1.485435986s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:13 coke ollama[52538]: time=2025-07-23T11:23:13.652+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 500 | 1.518564149s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 200 | 1.515248278s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.524962098s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.483078572s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.531772122s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.5405692s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 995.409951ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 983.57271ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 1.011495537s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:15 coke ollama[52538]: time=2025-07-23T11:23:15.515+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 500 | 1.061746777s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 1.020969104s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:15 coke ollama[52538]: time=2025-07-23T11:23:15.984+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 500 | 1.086227525s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 1.076547889s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 1.092751771s | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 870.377521ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 629.196721ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 569.56616ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 577.025258ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 474.75144ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 426.562036ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 391.478256ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 517.016915ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 577.389127ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:18 coke ollama[52538]: time=2025-07-23T11:23:18.339+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 500 | 656.875998ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 647.499798ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 677.261687ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 336.855412ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 287.985336ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 429.927135ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 480.333425ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 402.479508ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 371.925804ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 395.811701ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 423.629679ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 393.455793ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 371.444651ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 382.807879ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 388.908937ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 267.030666ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 338.740995ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 496.115634ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 349.800447ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 385.33025ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 474.095746ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:22 coke ollama[52538]: time=2025-07-23T11:23:22.886+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 500 | 505.948694ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 499.55023ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 354.626686ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 338.116327ms | 172.19.0.8 | POST "/api/embed"
7月 23 11:23:24 coke ollama[52538]: time=2025-07-23T11:23:24.328+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"
7月 23 11:23:24 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:24 | 500 | 452.260564ms | 172.19.0.8 | POST "/api/embed"

<!-- gh-comment-id:3105539484 --> @linabellbiu commented on GitHub (Jul 23, 2025): I encountered the same problem. (base) coke@coke:~/dify/docker$ journalctl -u ollama -f 7月 23 11:12:24 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:24 | 200 | 424.434928ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 441.649524ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 418.534893ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 200 | 397.615549ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:25 coke ollama[52538]: time=2025-07-23T11:12:25.802+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:12:25 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:25 | 500 | 496.054ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 200 | 521.802417ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 200 | 353.466301ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:12:26 coke ollama[52538]: time=2025-07-23T11:12:26.895+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:12:26 coke ollama[52538]: [GIN] 2025/07/23 - 11:12:26 | 500 | 452.757032ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:41 coke ollama[52538]: time=2025-07-23T11:22:41.980+08:00 level=INFO source=sched.go:788 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 gpu=GPU-6c63cf01-9a2d-4ccc-fbdd-e474b84adaae parallel=1 available=16599744512 required="5.9 GiB" 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.612+08:00 level=INFO source=server.go:135 msg="system memory" total="125.6 GiB" free="120.0 GiB" free_swap="8.0 GiB" 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.612+08:00 level=INFO source=server.go:175 msg=offload library=cuda layers.requested=-1 layers.model=37 layers.offload=37 layers.split="" memory.available="[15.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.9 GiB" memory.required.partial="5.9 GiB" memory.required.kv="576.0 MiB" memory.required.allocations="[5.9 GiB]" memory.weights.total="4.4 GiB" memory.weights.repeating="3.9 GiB" memory.weights.nonrepeating="486.0 MiB" memory.graph.full="384.0 MiB" memory.graph.partial="384.0 MiB" 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: loaded meta data with 36 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 (version GGUF V3 (latest)) 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 0: general.architecture str = qwen3 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 1: general.type str = model 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 4: general.size_label str = 8B 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 5: general.license str = apache-2.0 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 6: general.base_model.count u32 = 1 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 7: general.base_model.0.name str = Qwen3 8B Base 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 8: general.base_model.0.organization str = Qwen 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 9: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3-8B-... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 10: general.tags arr[str,5] = ["transformers", "sentence-transforme... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 11: qwen3.block_count u32 = 36 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 12: qwen3.context_length u32 = 40960 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 13: qwen3.embedding_length u32 = 4096 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 14: qwen3.feed_forward_length u32 = 12288 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 15: qwen3.attention.head_count u32 = 32 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 16: qwen3.attention.head_count_kv u32 = 8 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 17: qwen3.rope.freq_base f32 = 1000000.000000 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 18: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 19: qwen3.attention.key_length u32 = 128 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 20: qwen3.attention.value_length u32 = 128 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 21: qwen3.pooling_type u32 = 3 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 23: tokenizer.ggml.pre str = qwen2 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,151665] = ["!", "\"", "#", "$", "%", "&", "'", ... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 151643 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 28: tokenizer.ggml.padding_token_id u32 = 151643 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 29: tokenizer.ggml.eot_token_id u32 = 151645 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 31: tokenizer.ggml.add_eos_token bool = true 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 32: tokenizer.ggml.add_bos_token bool = false 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 33: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 34: general.quantization_version u32 = 2 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - kv 35: general.file_type u32 = 15 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type f32: 145 tensors 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type q4_K: 216 tensors 7月 23 11:22:42 coke ollama[52538]: llama_model_loader: - type q6_K: 37 tensors 7月 23 11:22:42 coke ollama[52538]: print_info: file format = GGUF V3 (latest) 7月 23 11:22:42 coke ollama[52538]: print_info: file type = Q4_K - Medium 7月 23 11:22:42 coke ollama[52538]: print_info: file size = 4.35 GiB (4.94 BPW) 7月 23 11:22:42 coke ollama[52538]: load: special tokens cache size = 22 7月 23 11:22:42 coke ollama[52538]: load: token to piece cache size = 0.9310 MB 7月 23 11:22:42 coke ollama[52538]: print_info: arch = qwen3 7月 23 11:22:42 coke ollama[52538]: print_info: vocab_only = 1 7月 23 11:22:42 coke ollama[52538]: print_info: model type = ?B 7月 23 11:22:42 coke ollama[52538]: print_info: model params = 7.57 B 7月 23 11:22:42 coke ollama[52538]: print_info: general.name = Qwen3 Embedding 8B 7月 23 11:22:42 coke ollama[52538]: print_info: vocab type = BPE 7月 23 11:22:42 coke ollama[52538]: print_info: n_vocab = 151665 7月 23 11:22:42 coke ollama[52538]: print_info: n_merges = 151387 7月 23 11:22:42 coke ollama[52538]: print_info: BOS token = 151643 '<|endoftext|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOS token = 151643 '<|endoftext|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOT token = 151645 '<|im_end|>' 7月 23 11:22:42 coke ollama[52538]: print_info: PAD token = 151643 '<|endoftext|>' 7月 23 11:22:42 coke ollama[52538]: print_info: LF token = 198 'Ċ' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM PRE token = 151659 '<|fim_prefix|>' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM SUF token = 151661 '<|fim_suffix|>' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM MID token = 151660 '<|fim_middle|>' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM PAD token = 151662 '<|fim_pad|>' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM REP token = 151663 '<|repo_name|>' 7月 23 11:22:42 coke ollama[52538]: print_info: FIM SEP token = 151664 '<|file_sep|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151643 '<|endoftext|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151645 '<|im_end|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151662 '<|fim_pad|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151663 '<|repo_name|>' 7月 23 11:22:42 coke ollama[52538]: print_info: EOG token = 151664 '<|file_sep|>' 7月 23 11:22:42 coke ollama[52538]: print_info: max token length = 256 7月 23 11:22:42 coke ollama[52538]: llama_model_load: vocab only - skipping tensors 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.911+08:00 level=INFO source=server.go:438 msg="starting llama server" cmd="/usr/local/bin/ollama runner --model /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 --ctx-size 4096 --batch-size 512 --n-gpu-layers 37 --threads 36 --parallel 1 --port 39047" 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=sched.go:483 msg="loaded runners" count=1 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=server.go:598 msg="waiting for llama runner to start responding" 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.912+08:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server not responding" 7月 23 11:22:42 coke ollama[52538]: time=2025-07-23T11:22:42.933+08:00 level=INFO source=runner.go:815 msg="starting go runner" 7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no 7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no 7月 23 11:22:43 coke ollama[52538]: ggml_cuda_init: found 1 CUDA devices: 7月 23 11:22:43 coke ollama[52538]: Device 0: Tesla V100-SXM2-16GB, compute capability 7.0, VMM: yes 7月 23 11:22:43 coke ollama[52538]: load_backend: loaded CUDA backend from /usr/local/lib/ollama/libggml-cuda.so 7月 23 11:22:43 coke ollama[52538]: load_backend: loaded CPU backend from /usr/local/lib/ollama/libggml-cpu-haswell.so 7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.044+08:00 level=INFO source=ggml.go:104 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 CUDA.0.ARCHS=500,600,610,700,750,800,860,870,890,900,1200 CUDA.0.USE_GRAPHS=1 CUDA.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(gcc) 7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.045+08:00 level=INFO source=runner.go:874 msg="Server listening on 127.0.0.1:39047" 7月 23 11:22:43 coke ollama[52538]: time=2025-07-23T11:22:43.164+08:00 level=INFO source=server.go:632 msg="waiting for server to become available" status="llm server loading model" 7月 23 11:22:43 coke ollama[52538]: llama_model_load_from_file_impl: using device CUDA0 (Tesla V100-SXM2-16GB) - 15830 MiB free 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: loaded meta data with 36 key-value pairs and 398 tensors from /usr/share/ollama/.ollama/models/blobs/sha256-3fcd3febec8b3fd64435204db75bf0dd73b91e8d0661e0331acfe7e7c3120b85 (version GGUF V3 (latest)) 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 0: general.architecture str = qwen3 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 1: general.type str = model 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 2: general.name str = Qwen3 Embedding 8B 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 3: general.basename str = Qwen3-Embedding 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 4: general.size_label str = 8B 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 5: general.license str = apache-2.0 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 6: general.base_model.count u32 = 1 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 7: general.base_model.0.name str = Qwen3 8B Base 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 8: general.base_model.0.organization str = Qwen 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 9: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3-8B-... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 10: general.tags arr[str,5] = ["transformers", "sentence-transforme... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 11: qwen3.block_count u32 = 36 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 12: qwen3.context_length u32 = 40960 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 13: qwen3.embedding_length u32 = 4096 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 14: qwen3.feed_forward_length u32 = 12288 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 15: qwen3.attention.head_count u32 = 32 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 16: qwen3.attention.head_count_kv u32 = 8 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 17: qwen3.rope.freq_base f32 = 1000000.000000 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 18: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 19: qwen3.attention.key_length u32 = 128 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 20: qwen3.attention.value_length u32 = 128 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 21: qwen3.pooling_type u32 = 3 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 23: tokenizer.ggml.pre str = qwen2 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,151665] = ["!", "\"", "#", "$", "%", "&", "'", ... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,151665] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 27: tokenizer.ggml.eos_token_id u32 = 151643 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 28: tokenizer.ggml.padding_token_id u32 = 151643 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 29: tokenizer.ggml.eot_token_id u32 = 151645 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 31: tokenizer.ggml.add_eos_token bool = true 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 32: tokenizer.ggml.add_bos_token bool = false 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 33: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 34: general.quantization_version u32 = 2 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - kv 35: general.file_type u32 = 15 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type f32: 145 tensors 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type q4_K: 216 tensors 7月 23 11:22:43 coke ollama[52538]: llama_model_loader: - type q6_K: 37 tensors 7月 23 11:22:43 coke ollama[52538]: print_info: file format = GGUF V3 (latest) 7月 23 11:22:43 coke ollama[52538]: print_info: file type = Q4_K - Medium 7月 23 11:22:43 coke ollama[52538]: print_info: file size = 4.35 GiB (4.94 BPW) 7月 23 11:22:43 coke ollama[52538]: load: special tokens cache size = 22 7月 23 11:22:43 coke ollama[52538]: load: token to piece cache size = 0.9310 MB 7月 23 11:22:43 coke ollama[52538]: print_info: arch = qwen3 7月 23 11:22:43 coke ollama[52538]: print_info: vocab_only = 0 7月 23 11:22:43 coke ollama[52538]: print_info: n_ctx_train = 40960 7月 23 11:22:43 coke ollama[52538]: print_info: n_embd = 4096 7月 23 11:22:43 coke ollama[52538]: print_info: n_layer = 36 7月 23 11:22:43 coke ollama[52538]: print_info: n_head = 32 7月 23 11:22:43 coke ollama[52538]: print_info: n_head_kv = 8 7月 23 11:22:43 coke ollama[52538]: print_info: n_rot = 128 7月 23 11:22:43 coke ollama[52538]: print_info: n_swa = 0 7月 23 11:22:43 coke ollama[52538]: print_info: n_swa_pattern = 1 7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_head_k = 128 7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_head_v = 128 7月 23 11:22:43 coke ollama[52538]: print_info: n_gqa = 4 7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_k_gqa = 1024 7月 23 11:22:43 coke ollama[52538]: print_info: n_embd_v_gqa = 1024 7月 23 11:22:43 coke ollama[52538]: print_info: f_norm_eps = 0.0e+00 7月 23 11:22:43 coke ollama[52538]: print_info: f_norm_rms_eps = 1.0e-06 7月 23 11:22:43 coke ollama[52538]: print_info: f_clamp_kqv = 0.0e+00 7月 23 11:22:43 coke ollama[52538]: print_info: f_max_alibi_bias = 0.0e+00 7月 23 11:22:43 coke ollama[52538]: print_info: f_logit_scale = 0.0e+00 7月 23 11:22:43 coke ollama[52538]: print_info: f_attn_scale = 0.0e+00 7月 23 11:22:43 coke ollama[52538]: print_info: n_ff = 12288 7月 23 11:22:43 coke ollama[52538]: print_info: n_expert = 0 7月 23 11:22:43 coke ollama[52538]: print_info: n_expert_used = 0 7月 23 11:22:43 coke ollama[52538]: print_info: causal attn = 1 7月 23 11:22:43 coke ollama[52538]: print_info: pooling type = 0 7月 23 11:22:43 coke ollama[52538]: print_info: rope type = 2 7月 23 11:22:43 coke ollama[52538]: print_info: rope scaling = linear 7月 23 11:22:43 coke ollama[52538]: print_info: freq_base_train = 1000000.0 7月 23 11:22:43 coke ollama[52538]: print_info: freq_scale_train = 1 7月 23 11:22:43 coke ollama[52538]: print_info: n_ctx_orig_yarn = 40960 7月 23 11:22:43 coke ollama[52538]: print_info: rope_finetuned = unknown 7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_conv = 0 7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_inner = 0 7月 23 11:22:43 coke ollama[52538]: print_info: ssm_d_state = 0 7月 23 11:22:43 coke ollama[52538]: print_info: ssm_dt_rank = 0 7月 23 11:22:43 coke ollama[52538]: print_info: ssm_dt_b_c_rms = 0 7月 23 11:22:43 coke ollama[52538]: print_info: model type = 8B 7月 23 11:22:43 coke ollama[52538]: print_info: model params = 7.57 B 7月 23 11:22:43 coke ollama[52538]: print_info: general.name = Qwen3 Embedding 8B 7月 23 11:22:43 coke ollama[52538]: print_info: vocab type = BPE 7月 23 11:22:43 coke ollama[52538]: print_info: n_vocab = 151665 7月 23 11:22:43 coke ollama[52538]: print_info: n_merges = 151387 7月 23 11:22:43 coke ollama[52538]: print_info: BOS token = 151643 '<|endoftext|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOS token = 151643 '<|endoftext|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOT token = 151645 '<|im_end|>' 7月 23 11:22:43 coke ollama[52538]: print_info: PAD token = 151643 '<|endoftext|>' 7月 23 11:22:43 coke ollama[52538]: print_info: LF token = 198 'Ċ' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM PRE token = 151659 '<|fim_prefix|>' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM SUF token = 151661 '<|fim_suffix|>' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM MID token = 151660 '<|fim_middle|>' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM PAD token = 151662 '<|fim_pad|>' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM REP token = 151663 '<|repo_name|>' 7月 23 11:22:43 coke ollama[52538]: print_info: FIM SEP token = 151664 '<|file_sep|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151643 '<|endoftext|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151645 '<|im_end|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151662 '<|fim_pad|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151663 '<|repo_name|>' 7月 23 11:22:43 coke ollama[52538]: print_info: EOG token = 151664 '<|file_sep|>' 7月 23 11:22:43 coke ollama[52538]: print_info: max token length = 256 7月 23 11:22:43 coke ollama[52538]: load_tensors: loading model tensors, this can take a while... (mmap = true) 7月 23 11:22:43 coke ollama[52538]: load_tensors: offloading 36 repeating layers to GPU 7月 23 11:22:43 coke ollama[52538]: load_tensors: offloading output layer to GPU 7月 23 11:22:43 coke ollama[52538]: load_tensors: offloaded 37/37 layers to GPU 7月 23 11:22:43 coke ollama[52538]: load_tensors: CUDA0 model buffer size = 4454.48 MiB 7月 23 11:22:43 coke ollama[52538]: load_tensors: CPU_Mapped model buffer size = 485.99 MiB 7月 23 11:22:44 coke ollama[52538]: llama_context: constructing llama_context 7月 23 11:22:44 coke ollama[52538]: llama_context: n_seq_max = 1 7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx = 4096 7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx_per_seq = 4096 7月 23 11:22:44 coke ollama[52538]: llama_context: n_batch = 512 7月 23 11:22:44 coke ollama[52538]: llama_context: n_ubatch = 512 7月 23 11:22:44 coke ollama[52538]: llama_context: causal_attn = 1 7月 23 11:22:44 coke ollama[52538]: llama_context: flash_attn = 0 7月 23 11:22:44 coke ollama[52538]: llama_context: freq_base = 1000000.0 7月 23 11:22:44 coke ollama[52538]: llama_context: freq_scale = 1 7月 23 11:22:44 coke ollama[52538]: llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized 7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA_Host output buffer size = 0.59 MiB 7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: kv_size = 4096, type_k = 'f16', type_v = 'f16', n_layer = 36, can_shift = 1, padding = 32 7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: CUDA0 KV buffer size = 576.00 MiB 7月 23 11:22:44 coke ollama[52538]: llama_kv_cache_unified: KV self size = 576.00 MiB, K (f16): 288.00 MiB, V (f16): 288.00 MiB 7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA0 compute buffer size = 304.22 MiB 7月 23 11:22:44 coke ollama[52538]: llama_context: CUDA_Host compute buffer size = 16.01 MiB 7月 23 11:22:44 coke ollama[52538]: llama_context: graph nodes = 1374 7月 23 11:22:44 coke ollama[52538]: llama_context: graph splits = 2 7月 23 11:22:44 coke ollama[52538]: time=2025-07-23T11:22:44.672+08:00 level=INFO source=server.go:637 msg="llama runner started in 1.76 seconds" 7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 3.95730585s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.097434459s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.307573308s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.669465537s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:45 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:45 | 200 | 4.804644006s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 4.904773446s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.134000884s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.228851286s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.341684237s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 5.400859549s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 1.689496291s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:46 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:46 | 200 | 1.678098205s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.686379843s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.538931326s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.724966529s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:47 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:47 | 200 | 1.917776609s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 1.956736046s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.012959536s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.188382936s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.246491936s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:48 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:48 | 200 | 2.135688918s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.120466654s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.121280637s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.061815222s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 2.023892558s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:49 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:49 | 200 | 1.85088303s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.8030479s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.987750466s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.946864034s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 1.931853169s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:50 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:50 | 200 | 2.015723593s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.989309472s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.922490633s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 2.0567454s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.868851876s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:51 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:51 | 200 | 1.967369102s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 2.014157439s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.678476458s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.818347551s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.827386364s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:52 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:52 | 200 | 1.958683725s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 1.964767401s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.147872275s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.002911678s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.106361414s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:53 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:53 | 200 | 2.020523508s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.986329621s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 2.157722921s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 2.056154139s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.898146904s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.750018525s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:54 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:54 | 200 | 1.792368105s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.682409342s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.729942534s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.718403339s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.806173898s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:55 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:55 | 200 | 1.835032129s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 1.956552307s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 1.838304157s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 2.117775535s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:56 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:56 | 200 | 2.065336634s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.059879619s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.182850753s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.242307876s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.057612019s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:57 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:57 | 200 | 2.050148604s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.066062286s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.05169877s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.259331386s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:58 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:58 | 200 | 2.146808913s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.157495167s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.169183221s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.045220267s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.08916033s | 172.19.0.8 | POST "/api/embed" 7月 23 11:22:59 coke ollama[52538]: [GIN] 2025/07/23 - 11:22:59 | 200 | 2.271678594s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.242806503s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.206771551s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 2.112279391s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 1.972523275s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:00 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:00 | 200 | 1.966753362s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 1.968742495s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.111598758s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.118126409s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:01 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:01 | 200 | 2.12256577s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.137052163s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 1.977210664s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.129386198s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.104305861s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:02 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:02 | 200 | 2.25898748s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.22796644s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.377335482s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.229183565s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.144004666s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:03 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:03 | 200 | 2.045762367s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.096489163s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.397861259s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.294938882s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:04 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:04 | 200 | 2.270212051s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.093897672s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.133588129s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 1.89427208s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.020326876s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:05 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:05 | 200 | 2.108986163s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 2.15937526s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 2.10358666s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 1.954297774s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:06 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:06 | 200 | 1.918591215s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.067281978s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.079225175s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 1.906419489s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.09282623s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 2.037115116s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:07 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:07 | 200 | 1.929813435s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 1.904462873s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 1.920355956s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 2.026594488s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:08 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:08 | 200 | 2.182131606s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.057251869s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.084850578s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.377947553s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:09 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:09 | 200 | 2.375754502s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 200 | 2.386479444s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 200 | 2.4657119s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.549+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.471647682s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.761+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.451126228s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:10 coke ollama[52538]: time=2025-07-23T11:23:10.929+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:10 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:10 | 500 | 2.297690143s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.201706198s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.353981302s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.377790703s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:11 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:11 | 200 | 2.177294558s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.189870298s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.099538443s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 2.103157126s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 1.520879897s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:12 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:12 | 200 | 1.312047266s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 200 | 1.325906987s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:13 coke ollama[52538]: time=2025-07-23T11:23:13.390+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 500 | 1.485435986s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:13 coke ollama[52538]: time=2025-07-23T11:23:13.652+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 500 | 1.518564149s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:13 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:13 | 200 | 1.515248278s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.524962098s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.483078572s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.531772122s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 1.5405692s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:14 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:14 | 200 | 995.409951ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 983.57271ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 1.011495537s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:15 coke ollama[52538]: time=2025-07-23T11:23:15.515+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 500 | 1.061746777s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 200 | 1.020969104s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:15 coke ollama[52538]: time=2025-07-23T11:23:15.984+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:15 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:15 | 500 | 1.086227525s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 1.076547889s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 1.092751771s | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 870.377521ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:16 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:16 | 200 | 629.196721ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 569.56616ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 577.025258ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 474.75144ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 426.562036ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 391.478256ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:17 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:17 | 200 | 517.016915ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 577.389127ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:18 coke ollama[52538]: time=2025-07-23T11:23:18.339+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 500 | 656.875998ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 647.499798ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 677.261687ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:18 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:18 | 200 | 336.855412ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 287.985336ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 429.927135ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 480.333425ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:19 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:19 | 200 | 402.479508ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 371.925804ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 395.811701ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 423.629679ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 393.455793ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:20 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:20 | 200 | 371.444651ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 382.807879ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 388.908937ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 267.030666ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 338.740995ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:21 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:21 | 200 | 496.115634ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 349.800447ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 385.33025ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 200 | 474.095746ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:22 coke ollama[52538]: time=2025-07-23T11:23:22.886+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:22 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:22 | 500 | 505.948694ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 499.55023ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 354.626686ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:23 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:23 | 200 | 338.116327ms | 172.19.0.8 | POST "/api/embed" 7月 23 11:23:24 coke ollama[52538]: time=2025-07-23T11:23:24.328+08:00 level=INFO source=server.go:946 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" 7月 23 11:23:24 coke ollama[52538]: [GIN] 2025/07/23 - 11:23:24 | 500 | 452.260564ms | 172.19.0.8 | POST "/api/embed"

GiteaMirror commented 2026-04-12 17:43:48 -05:00

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@mcr-ksh commented on GitHub (Dec 24, 2025):

+1

just ran into this after updating the Ollama to the lastest 0.13.5. Used to work flawless in an n8n workflow.

Before the error I got:
"init: embeddings required but some input tokens were not marked as outputs -> overriding"

<!-- gh-comment-id:3689841252 --> @mcr-ksh commented on GitHub (Dec 24, 2025): +1 just ran into this after updating the Ollama to the lastest 0.13.5. Used to work flawless in an n8n workflow. Before the error I got: "init: embeddings required but some input tokens were not marked as outputs -> overriding"

GiteaMirror commented 2026-04-12 17:43:48 -05:00

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@nicho2 commented on GitHub (Jan 15, 2026):

I've ollama version 0.13.4

I just received this:

POST /api/embed HTTP/1.1
Host: 10.2.142.77:11434
User-Agent: python-requests/2.32.5
Accept-Encoding: gzip, deflate
Accept: */*
Connection: keep-alive
Content-Type: application/json
Content-Length: 202

{"input": ["This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such."], "model": "bge-m3:latest", "options": {"use_mmap": true}}


HTTP/1.1 500 Internal Server Error
Content-Type: application/json; charset=utf-8
Date: Thu, 15 Jan 2026 12:49:57 GMT
Content-Length: 67

{"error":"failed to encode response: json: unsupported value: NaN"}

-Log:

init: embeddings required but some input tokens were not marked as outputs -> overriding

[GIN] 2026/01/15 - 12:49:57 | 200 |  124.310228ms |      172.21.0.1 | POST     "/api/embed"

time=2026-01-15T12:49:57.196Z level=DEBUG source=sched.go:385 msg="context for request finished" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096

time=2026-01-15T12:49:57.197Z level=DEBUG source=sched.go:290 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 duration=8m0s

time=2026-01-15T12:49:57.197Z level=DEBUG source=sched.go:308 msg="after processing request finished event" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 refCount=0

time=2026-01-15T12:49:57.332Z level=DEBUG source=sched.go:626 msg="evaluating already loaded" model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c

time=2026-01-15T12:49:57.360Z level=DEBUG source=ggml.go:281 msg="key with type not found" key=general.alignment default=32

time=2026-01-15T12:49:57.362Z level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=359 prompt=29 used=0 remaining=29

decode: cannot decode batches with this context (calling encode() instead)

init: embeddings required but some input tokens were not marked as outputs -> overriding

time=2026-01-15T12:49:57.367Z level=INFO source=server.go:1724 msg="llm embedding error: failed to encode response: json: unsupported value: NaN"

[GIN] 2026/01/15 - 12:49:57 | 500 |   129.39789ms |      172.21.0.1 | POST     "/api/embed"

time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:385 msg="context for request finished" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096

time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:290 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 duration=8m0s

time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:308 msg="after processing request finished event" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 refCount=0

<!-- gh-comment-id:3754680330 --> @nicho2 commented on GitHub (Jan 15, 2026): I've ollama version 0.13.4 I just received this: POST /api/embed HTTP/1.1 Host: 10.2.142.77:11434 User-Agent: python-requests/2.32.5 Accept-Encoding: gzip, deflate Accept: */* Connection: keep-alive Content-Type: application/json Content-Length: 202 {"input": ["This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such."], "model": "bge-m3:latest", "options": {"use_mmap": true}} HTTP/1.1 500 Internal Server Error Content-Type: application/json; charset=utf-8 Date: Thu, 15 Jan 2026 12:49:57 GMT Content-Length: 67 {"error":"failed to encode response: json: unsupported value: NaN"} -Log: init: embeddings required but some input tokens were not marked as outputs -> overriding [GIN] 2026/01/15 - 12:49:57 | 200 | 124.310228ms | 172.21.0.1 | POST "/api/embed" time=2026-01-15T12:49:57.196Z level=DEBUG source=sched.go:385 msg="context for request finished" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 time=2026-01-15T12:49:57.197Z level=DEBUG source=sched.go:290 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 duration=8m0s time=2026-01-15T12:49:57.197Z level=DEBUG source=sched.go:308 msg="after processing request finished event" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 refCount=0 time=2026-01-15T12:49:57.332Z level=DEBUG source=sched.go:626 msg="evaluating already loaded" model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c time=2026-01-15T12:49:57.360Z level=DEBUG source=ggml.go:281 msg="key with type not found" key=general.alignment default=32 time=2026-01-15T12:49:57.362Z level=DEBUG source=cache.go:104 msg="loading cache slot" id=0 cache=359 prompt=29 used=0 remaining=29 decode: cannot decode batches with this context (calling encode() instead) init: embeddings required but some input tokens were not marked as outputs -> overriding time=2026-01-15T12:49:57.367Z level=INFO source=server.go:1724 msg="llm embedding error: failed to encode response: json: unsupported value: NaN" [GIN] 2026/01/15 - 12:49:57 | 500 | 129.39789ms | 172.21.0.1 | POST "/api/embed" time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:385 msg="context for request finished" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:290 msg="runner with non-zero duration has gone idle, adding timer" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 duration=8m0s time=2026-01-15T12:49:57.368Z level=DEBUG source=sched.go:308 msg="after processing request finished event" runner.name=registry.ollama.ai/library/bge-m3:latest runner.inference="[{ID:GPU-45972459-815c-f304-9fdf-b952276c9b13 Library:CUDA}]" runner.size="1.1 GiB" runner.vram="1.1 GiB" runner.parallel=1 runner.pid=10997 runner.model=/root/.ollama/models/blobs/sha256-daec91ffb5dd0c27411bd71f29932917c49cf529a641d0168496c3a501e3062c runner.num_ctx=4096 refCount=0

GiteaMirror commented 2026-04-12 17:43:49 -05:00

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@nicho2 commented on GitHub (Jan 15, 2026):

same thing in 0.14.0

but

when i send :
curl http://10.2.142.77:11434/api/embed -d '{
"model": "bge-m3:latest",
"input": "This document is a draft distributed for approval."
}'
it's OK:

POST /api/embed HTTP/1.1
Host: 10.2.142.77:11434
User-Agent: curl/7.81.0
Accept: */*
Content-Length: 95
Content-Type: application/x-www-form-urlencoded

{
  "model": "bge-m3:latest",
  "input": "This document is a draft distributed for approval."
}
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
Date: Thu, 15 Jan 2026 13:16:49 GMT
Transfer-Encoding: chunked

{"model":"bge-m3:latest","embeddings":[[-0.015445454,0.003276025,-0.032736298,0.008763502,-0.0253346,-0.05621706,0.060042914,0.013629458,0.012102511,0.01625889,-0.0021870725,-0.01320955,-0.010680699,-0.00022075947,0.018077575,0.004602876,0.050414875,-0.02080775,-0.027023934,-0.002845781,-0.030523593,0.011803625,0.040470228,0.024725655,-0.047343507,0.022378556,-0.016207317,-0.001203077,0.03228503,0.02187892,0.018690186,-0.01785771,0.029428432,-0.024072818,0.0045784162,-0.044287648,-0.013129439,-0.033630155,-0.030983737,0.023344262,-0.012560762,-0.0078084823,0.021287857,-0.061550602,0.019530142,0.011605382,0.00019195586,-0.022348104,-0.025308289,-0.0028609901,-0.031649172,0.023210876,0.056044046,-0.026173636,0.02812822,0.0037022,0.021429488,-0.019578056,-0.0845583,0.023569038,-0.044206563,-0.0113979485,-0.0103847,-0.008856806,0.020307465,0.06085907,0.048012324,0.009598146,-0.024038533,-0.017801082,-0.008899206,0.032167103,-0.02682478,0.0007035052,-0.056625433,0.021817239,0.032399602,-0.07642074,0.0036620772,0.058536515,0.008637845,-0.009830092,0.01197731,0.007796856,-0.054444678,-0.0076599023,-0.047528476,0.039386824,0.019119918,-0.009168872,-0.034833595,0.015555431,0.036482897,-0.026195176,-0.03490326,0.01288963,-0.076935954,-0.004761672,0.0074276295,0.013270374,0.027959965,0.021551395,-0.009471928,-0.010893856,0.002629465,-0.019170653,0.039675627,0.011736331,0.04628006,-0.008328642,-0.011577215,0.005860599,0.033464115,-0.018660733,0.01838674,-0.007907991,-0.016121991,-0.03981626,-0.015577496,-0.0021521072,0.0028034544,0.0076389913,0.049580887,-0.029046664,0.013811698,-0.048230592,0.019610893,0.039051075,0.0260056,-0.014266633,0.04694729,0.064460024,-0.014719029,-0.023613526,-0.032929454,-0.02090901,-0.03304115,0.021721477,0.0021194443,-0.034874875,0.07790756,0.012337135,-0.045040157,-0.026725331,0.057313863,-0.1025184,0.038194004,-0.01808049,0.03202347,0.004171357,0.014145894,0.022467604,0.0084766345,-0.0104922885,0.05689718,-0.03424302,0.015268611,0.019957358,0.0132919345,0.06806766,-0.028033918,0.029516596,-0.017997397,-0.020068994,-0.0009792305,0.01766953,0.029603066,0.06188093,-0.010562154,-0.06265268,-0.000027546368,-0.0031017687,0.04113726,-0.022804378,0.01585459,0.026730621,0.047201797,-0.0032959513,0.0022920186,-0.05411061,-0.019644663,0.031293236,-0.012883818,-0.026349872,-0.008244882,-0.00010930865,0.011371867,-0.020588009,-0.012020719,-0.02025077,-0.021215668,-0.032841977,0.0034183662,0.001374491,-0.009573052,-0.025447372,-0.027364759,-0.048350755,-0.010890413,-0.068638876,-0.026589585,0.029143576,0.07048744,0.0071354685,-0.014211876,-0.026391614,-0.027603779,-0.028470699,0.017523188,-0.040969852,-0.057280704,-0.0020852506,-0.0043937746,-0.011291085,-0.011979187,0.034178134,0.028641421,0.011618161,0.010678629,-0.030960325,-0.032818086,0.007113562,0.021895787,0.058146212,0.009214191,0.005038449,-0.007188165,0.024632165,0.031550083,-0.057382002,-0.039669264,-0.0020119057,-0.019224258,-0.040861137,0.07563455,0.0095492825,-0.014664481,0.024950933,0.018580398,0.005288304,-0.012328877,0.0102612525,0.0119015025,-0.03538505,-0.04062535,0.029592982,-0.034370214,0.029243223,-0.03107611,-0.0019364593,0.023855047,-0.0009654886,-0.03617323,0.025261872,0.0060371687,0.01842621,-0.017190982,-0.0027674527,0.006770897,-0.0065281377,0.023136081,-0.03553879,0.01712718,0.03552223,0.036402587,-0.01579471,-0.033217978,0.011281189,0.030687224,-0.053479318,0.003708311,-0.026924105,0.016295,-0.015588822,0.034735266,-0.0038257819,-0.0133855445,-0.0045978953,0.036552515,-0.019900836,-0.016232884,0.048368648,0.026970956,-0.013713893,0.030491758,0.006877708,-0.008417689,-0.021315278,0.036123082,-0.011471454,-0.01975225,-0.004748489,0.058369484,-0.021009754,-0.023229802,0.01102451,-0.0082925875,-0.16528273,0.00863624,-0.004970701,-0.031583283,0.0069563654,-0.018628025,-0.035674002,-0.013911859,-0.000086524225,0.053010687,0.035070438,-0.04878839,0.018753966,0.037815135,0.01555174,0.015058085,-0.008200825,0.0029965467,-0.00072948914,0.00010433371,-0.02442157,-0.021330282,0.10416154,0.0069224103,-0.041053694,0.016387695,0.037728645,0.0024058563,-0.042805858,0.026593184,0.008263658,0.009043465,-0.0067615905,0.0076865233,-0.0040431404,0.040152516,0.05020241,-0.011230476,-0.020675005,-0.021936446,0.01432799,0.03975448,-0.016602222,0.03745323,-0.0051519643,-0.00832569,0.020547722,0.0022187612,-0.019729288,-0.009041786,-0.006680888,-0.012119521,-0.02245279,-0.011801761,-0.07318276,-0.008810027,-0.043800347,0.01201429,-0.052644923,0.055857368,-0.024241354,-0.061781283,0.021951046,-0.00045822386,-0.038456485,-0.00041926446,0.04600639,-0.011969451,0.0047146957,-0.015729569,0.023674335,-0.017260734,0.03086358,-0.022705378,0.017492127,0.023114882,0.0075497935,0.008272093,-0.031016277,-0.09495582,0.010780377,0.0034350043,-0.011891655,-0.016835637,-0.025169417,-0.017145382,-0.0024130016,0.005594143,0.08055568,0.25624886,-0.016478673,0.040600453,-0.02800638,0.06633598,-0.047079153,-0.008968846,-0.004289243,-0.027616,-0.03401705,0.018262355,-0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When i send :

curl http://10.2.142.77:11434/api/embed -d '{
"model": "bge-m3:latest",
"input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such."
}'

it's fail:

POST /api/embed HTTP/1.1
Host: 10.2.142.77:11434
User-Agent: curl/7.81.0
Accept: */*
Content-Length: 175
Content-Type: application/x-www-form-urlencoded

{
  "model": "bge-m3:latest",
  "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such."
}
HTTP/1.1 500 Internal Server Error
Content-Type: application/json; charset=utf-8
Date: Thu, 15 Jan 2026 13:21:54 GMT
Content-Length: 67

{"error":"failed to encode response: json: unsupported value: NaN"}

same thing in only-cpu

<!-- gh-comment-id:3754808126 --> @nicho2 commented on GitHub (Jan 15, 2026): same thing in 0.14.0 but when i send : curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval." }' it's OK: POST /api/embed HTTP/1.1 Host: 10.2.142.77:11434 User-Agent: curl/7.81.0 Accept: */* Content-Length: 95 Content-Type: application/x-www-form-urlencoded { "model": "bge-m3:latest", "input": "This document is a draft distributed for approval." } HTTP/1.1 200 OK Content-Type: application/json; charset=utf-8 Date: Thu, 15 Jan 2026 13:16:49 GMT Transfer-Encoding: chunked 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When i send : curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such." }' it's fail: POST /api/embed HTTP/1.1 Host: 10.2.142.77:11434 User-Agent: curl/7.81.0 Accept: */* Content-Length: 175 Content-Type: application/x-www-form-urlencoded { "model": "bge-m3:latest", "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such." } HTTP/1.1 500 Internal Server Error Content-Type: application/json; charset=utf-8 Date: Thu, 15 Jan 2026 13:21:54 GMT Content-Length: 67 {"error":"failed to encode response: json: unsupported value: NaN"} same thing in only-cpu

GiteaMirror commented 2026-04-12 17:43:50 -05:00

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@shihkauskas commented on GitHub (Mar 2, 2026):

same thing in 0.14.0

but

when i send : curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval." }' it's OK:

POST /api/embed HTTP/1.1
Host: 10.2.142.77:11434
User-Agent: curl/7.81.0
Accept: */*
Content-Length: 95
Content-Type: application/x-www-form-urlencoded

{
  "model": "bge-m3:latest",
  "input": "This document is a draft distributed for approval."
}
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
Date: Thu, 15 Jan 2026 13:16:49 GMT
Transfer-Encoding: chunked

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When i send :

curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such." }'

it's fail:

POST /api/embed HTTP/1.1
Host: 10.2.142.77:11434
User-Agent: curl/7.81.0
Accept: */*
Content-Length: 175
Content-Type: application/x-www-form-urlencoded

{
  "model": "bge-m3:latest",
  "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such."
}
HTTP/1.1 500 Internal Server Error
Content-Type: application/json; charset=utf-8
Date: Thu, 15 Jan 2026 13:21:54 GMT
Content-Length: 67

{"error":"failed to encode response: json: unsupported value: NaN"}

same thing in only-cpu

the same error in version 0.17.0

<!-- gh-comment-id:3983668511 --> @shihkauskas commented on GitHub (Mar 2, 2026): > same thing in 0.14.0 > > but > > when i send : curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval." }' it's OK: > > ``` > POST /api/embed HTTP/1.1 > Host: 10.2.142.77:11434 > User-Agent: curl/7.81.0 > Accept: */* > Content-Length: 95 > Content-Type: application/x-www-form-urlencoded > > { > "model": "bge-m3:latest", > "input": "This document is a draft distributed for approval." > } > HTTP/1.1 200 OK > Content-Type: application/json; charset=utf-8 > Date: Thu, 15 Jan 2026 13:16:49 GMT > Transfer-Encoding: chunked > > 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> ``` > > When i send : > > curl http://10.2.142.77:11434/api/embed -d '{ "model": "bge-m3:latest", "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such." }' > > it's fail: > > ``` > POST /api/embed HTTP/1.1 > Host: 10.2.142.77:11434 > User-Agent: curl/7.81.0 > Accept: */* > Content-Length: 175 > Content-Type: application/x-www-form-urlencoded > > { > "model": "bge-m3:latest", > "input": "This document is a draft distributed for approval. It may not be referred to as an International Standard until published as such." > } > HTTP/1.1 500 Internal Server Error > Content-Type: application/json; charset=utf-8 > Date: Thu, 15 Jan 2026 13:21:54 GMT > Content-Length: 67 > > {"error":"failed to encode response: json: unsupported value: NaN"} > ``` > > same thing in only-cpu the same error in version 0.17.0

GiteaMirror referenced this issue 2026-04-12 23:48:37 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #12072

GiteaMirror referenced this issue 2026-04-16 06:00:09 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #17343

GiteaMirror referenced this issue 2026-04-19 16:26:23 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #22612

GiteaMirror referenced this issue 2026-04-22 22:36:39 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #37945

GiteaMirror referenced this issue 2026-04-24 22:57:58 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #43320

GiteaMirror referenced this issue 2026-04-29 13:40:15 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #58769

GiteaMirror referenced this issue 2026-05-05 06:24:53 -05:00

[PR #6290] [MERGED] Harden intel boostrap for nil pointers #74366

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parth-copilot-token-length-defaults

hoyyeva/poolside-windows

laguna-support

jmorganca/harden-markdown-rendering

laguna-renderer-parser

laguna-llamacpp

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v0.5.3

v0.5.3-rc0

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Reference: github-starred/ollama#6290