[GH-ISSUE #9870] After update a few days ago the program stopped working. Before that everything was fine. #32223

New Issue

GiteaMirror · 2026-04-22T13:16:59-05:00

GiteaMirror commented

2026-04-22 13:16:59 -05:00

Originally created by @Oleg777778 on GitHub (Mar 18, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9870

What is the issue?

After update a few days ago the program stopped working. Before that everything was fine.

C:\Windows\SysWOW64>ollama run mistral:7b
pulling manifest
pulling ff82381e2bea... 100% ▕████████████████████████████████████████████████████████▏ 4.1 GB
pulling 43070e2d4e53... 100% ▕████████████████████████████████████████████████████████▏ 11 KB
pulling 491dfa501e59... 100% ▕████████████████████████████████████████████████████████▏ 801 B
pulling ed11eda7790d... 100% ▕████████████████████████████████████████████████████████▏ 30 B
pulling 42347cd80dc8... 100% ▕████████████████████████████████████████████████████████▏ 485 B
verifying sha256 digest
writing manifest
success

help
Error: POST predict: Post "http://127.0.0.1:5422/completion": read tcp 127.0.0.1:5424->127.0.0.1:5422: wsarecv: An existing connection was forcibly closed by the remote host.

C:\Windows\SysWOW64>ollama run mistral:7b

What is your name?
Error: POST predict: Post "http://127.0.0.1:5432/completion": read tcp 127.0.0.1:5434->127.0.0.1:5432: wsarecv: An existing connection was forcibly closed by the remote host.

C:\Windows\SysWOW64>

Relevant log output

2025/03/18 22:55:25 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\Oleg\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-03-18T22:55:25.261+03:00 level=INFO source=images.go:432 msg="total blobs: 0"
time=2025-03-18T22:55:25.261+03:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0"
time=2025-03-18T22:55:25.261+03:00 level=INFO source=routes.go:1297 msg="Listening on 127.0.0.1:11434 (version 0.6.2)"
time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=6 efficiency=0 threads=12
time=2025-03-18T22:55:25.414+03:00 level=INFO source=gpu.go:377 msg="no compatible GPUs were discovered"
time=2025-03-18T22:55:25.414+03:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=cpu variant="" compute="" driver=0.0 name="" total="64.0 GiB" available="56.2 GiB"
[GIN] 2025/03/18 - 23:01:18 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2025/03/18 - 23:01:18 | 404 |      1.0512ms |       127.0.0.1 | POST     "/api/show"
time=2025-03-18T23:01:19.012+03:00 level=INFO source=download.go:176 msg="downloading ff82381e2bea in 16 257 MB part(s)"
time=2025-03-18T23:02:20.558+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 13 attempt 0 failed: unexpected EOF, retrying in 1s"
time=2025-03-18T23:03:06.564+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 14 attempt 0 failed: unexpected EOF, retrying in 1s"
time=2025-03-18T23:04:46.789+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 2 attempt 0 failed: unexpected EOF, retrying in 1s"
time=2025-03-18T23:07:21.559+03:00 level=INFO source=download.go:176 msg="downloading 43070e2d4e53 in 1 11 KB part(s)"
time=2025-03-18T23:07:22.951+03:00 level=INFO source=download.go:176 msg="downloading 491dfa501e59 in 1 801 B part(s)"
time=2025-03-18T23:07:24.355+03:00 level=INFO source=download.go:176 msg="downloading ed11eda7790d in 1 30 B part(s)"
time=2025-03-18T23:07:25.755+03:00 level=INFO source=download.go:176 msg="downloading 42347cd80dc8 in 1 485 B part(s)"
[GIN] 2025/03/18 - 23:07:30 | 200 |         6m12s |       127.0.0.1 | POST     "/api/pull"
[GIN] 2025/03/18 - 23:07:30 | 200 |      7.5122ms |       127.0.0.1 | POST     "/api/show"
time=2025-03-18T23:07:30.463+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.4 GiB" free_swap="54.7 GiB"
time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0
time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128
time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128
time=2025-03-18T23:07:30.463+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.4 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 1
print_info: model type       = ?B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
llama_model_load: vocab only - skipping tensors
time=2025-03-18T23:07:30.514+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 9906"
time=2025-03-18T23:07:30.518+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-18T23:07:30.518+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-03-18T23:07:30.519+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-03-18T23:07:30.545+03:00 level=INFO source=runner.go:846 msg="starting go runner"
load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
time=2025-03-18T23:07:30.592+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2025-03-18T23:07:30.593+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:9906"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 4096
print_info: n_layer          = 32
print_info: n_head           = 32
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 4
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: n_ff             = 14336
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 7B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors:          CPU model buffer size =  3922.02 MiB
time=2025-03-18T23:07:30.770+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
llama_init_from_model: n_seq_max     = 4
llama_init_from_model: n_ctx         = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch       = 2048
llama_init_from_model: n_ubatch      = 512
llama_init_from_model: flash_attn    = 0
llama_init_from_model: freq_base     = 1000000.0
llama_init_from_model: freq_scale    = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1
llama_kv_cache_init:        CPU KV buffer size =  1024.00 MiB
llama_init_from_model: KV self size  = 1024.00 MiB, K (f16):  512.00 MiB, V (f16):  512.00 MiB
llama_init_from_model:        CPU  output buffer size =     0.56 MiB
llama_init_from_model:        CPU compute buffer size =   560.01 MiB
llama_init_from_model: graph nodes  = 1030
llama_init_from_model: graph splits = 1
time=2025-03-18T23:07:32.274+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.76 seconds"
[GIN] 2025/03/18 - 23:07:32 | 200 |    1.8312845s |       127.0.0.1 | POST     "/api/generate"
C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed
[GIN] 2025/03/18 - 23:10:03 | 200 |     11.2662ms |       127.0.0.1 | POST     "/api/chat"
time=2025-03-18T23:10:03.934+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"
[GIN] 2025/03/18 - 23:14:48 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2025/03/18 - 23:14:48 | 404 |       512.2µs |       127.0.0.1 | POST     "/api/show"
[GIN] 2025/03/18 - 23:14:49 | 200 |    999.2685ms |       127.0.0.1 | POST     "/api/pull"
[GIN] 2025/03/18 - 23:14:49 | 200 |     13.5051ms |       127.0.0.1 | POST     "/api/show"
time=2025-03-18T23:14:49.699+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.4 GiB" free_swap="54.8 GiB"
time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0
time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128
time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128
time=2025-03-18T23:14:49.700+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.4 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 1
print_info: model type       = ?B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
llama_model_load: vocab only - skipping tensors
time=2025-03-18T23:14:49.744+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 5422"
time=2025-03-18T23:14:49.748+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-18T23:14:49.748+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-03-18T23:14:49.748+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-03-18T23:14:49.782+03:00 level=INFO source=runner.go:846 msg="starting go runner"
load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
time=2025-03-18T23:14:49.828+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2025-03-18T23:14:49.829+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:5422"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 4096
print_info: n_layer          = 32
print_info: n_head           = 32
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 4
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: n_ff             = 14336
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 7B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors:          CPU model buffer size =  3922.02 MiB
time=2025-03-18T23:14:50.000+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
llama_init_from_model: n_seq_max     = 4
llama_init_from_model: n_ctx         = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch       = 2048
llama_init_from_model: n_ubatch      = 512
llama_init_from_model: flash_attn    = 0
llama_init_from_model: freq_base     = 1000000.0
llama_init_from_model: freq_scale    = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1
llama_kv_cache_init:        CPU KV buffer size =  1024.00 MiB
llama_init_from_model: KV self size  = 1024.00 MiB, K (f16):  512.00 MiB, V (f16):  512.00 MiB
llama_init_from_model:        CPU  output buffer size =     0.56 MiB
llama_init_from_model:        CPU compute buffer size =   560.01 MiB
llama_init_from_model: graph nodes  = 1030
llama_init_from_model: graph splits = 1
time=2025-03-18T23:14:51.503+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.75 seconds"
[GIN] 2025/03/18 - 23:14:51 | 200 |    1.8278445s |       127.0.0.1 | POST     "/api/generate"
C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed
[GIN] 2025/03/18 - 23:15:16 | 200 |     11.1082ms |       127.0.0.1 | POST     "/api/chat"
time=2025-03-18T23:15:16.613+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"
[GIN] 2025/03/18 - 23:15:45 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2025/03/18 - 23:15:45 | 200 |      8.2655ms |       127.0.0.1 | POST     "/api/show"
time=2025-03-18T23:15:45.304+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.3 GiB" free_swap="54.7 GiB"
time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0
time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128
time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128
time=2025-03-18T23:15:45.304+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 1
print_info: model type       = ?B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
llama_model_load: vocab only - skipping tensors
time=2025-03-18T23:15:45.351+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 5432"
time=2025-03-18T23:15:45.355+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-18T23:15:45.355+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-03-18T23:15:45.355+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-03-18T23:15:45.382+03:00 level=INFO source=runner.go:846 msg="starting go runner"
load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
time=2025-03-18T23:15:45.426+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2025-03-18T23:15:45.427+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:5432"
llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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              = llama
llama_model_loader: - kv   1:                               general.name str              = Mistral-7B-Instruct-v0.3
llama_model_loader: - kv   2:                          llama.block_count u32              = 32
llama_model_loader: - kv   3:                       llama.context_length u32              = 32768
llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 2
llama_model_loader: - kv  11:                           llama.vocab_size u32              = 32768
llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = default
llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,32768]   = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv  16:                      tokenizer.ggml.scores arr[f32,32768]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  17:                  tokenizer.ggml.token_type arr[i32,32768]   = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  20:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  21:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  22:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  23:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
llama_model_loader: - kv  24:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_0
print_info: file size   = 3.83 GiB (4.54 BPW) 
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 771
load: token to piece cache size = 0.1731 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 4096
print_info: n_layer          = 32
print_info: n_head           = 32
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 4
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: n_ff             = 14336
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 7B
print_info: model params     = 7.25 B
print_info: general.name     = Mistral-7B-Instruct-v0.3
print_info: vocab type       = SPM
print_info: n_vocab          = 32768
print_info: n_merges         = 0
print_info: BOS token        = 1 '<s>'
print_info: EOS token        = 2 '</s>'
print_info: UNK token        = 0 '<unk>'
print_info: LF token         = 781 '<0x0A>'
print_info: EOG token        = 2 '</s>'
print_info: max token length = 48
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors:          CPU model buffer size =  3922.02 MiB
time=2025-03-18T23:15:45.606+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
llama_init_from_model: n_seq_max     = 4
llama_init_from_model: n_ctx         = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch       = 2048
llama_init_from_model: n_ubatch      = 512
llama_init_from_model: flash_attn    = 0
llama_init_from_model: freq_base     = 1000000.0
llama_init_from_model: freq_scale    = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1
llama_kv_cache_init:        CPU KV buffer size =  1024.00 MiB
llama_init_from_model: KV self size  = 1024.00 MiB, K (f16):  512.00 MiB, V (f16):  512.00 MiB
llama_init_from_model:        CPU  output buffer size =     0.56 MiB
llama_init_from_model:        CPU compute buffer size =   560.01 MiB
llama_init_from_model: graph nodes  = 1030
llama_init_from_model: graph splits = 1
time=2025-03-18T23:15:47.109+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.75 seconds"
[GIN] 2025/03/18 - 23:15:47 | 200 |      1.82761s |       127.0.0.1 | POST     "/api/generate"
C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed
[GIN] 2025/03/18 - 23:16:27 | 200 |     10.8311ms |       127.0.0.1 | POST     "/api/chat"
time=2025-03-18T23:16:27.219+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"
[GIN] 2025/03/18 - 23:21:43 | 200 |            0s |       127.0.0.1 | GET      "/api/version"

OS

Windows

GPU

AMD

CPU

AMD

Ollama version

0.6.2

Originally created by @Oleg777778 on GitHub (Mar 18, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9870 ### What is the issue? After update a few days ago the program stopped working. Before that everything was fine. C:\Windows\SysWOW64>ollama run mistral:7b pulling manifest pulling ff82381e2bea... 100% ▕████████████████████████████████████████████████████████▏ 4.1 GB pulling 43070e2d4e53... 100% ▕████████████████████████████████████████████████████████▏ 11 KB pulling 491dfa501e59... 100% ▕████████████████████████████████████████████████████████▏ 801 B pulling ed11eda7790d... 100% ▕████████████████████████████████████████████████████████▏ 30 B pulling 42347cd80dc8... 100% ▕████████████████████████████████████████████████████████▏ 485 B verifying sha256 digest writing manifest success >>> help Error: POST predict: Post "http://127.0.0.1:5422/completion": read tcp 127.0.0.1:5424->127.0.0.1:5422: wsarecv: An existing connection was forcibly closed by the remote host. C:\Windows\SysWOW64>ollama run mistral:7b >>> What is your name? Error: POST predict: Post "http://127.0.0.1:5432/completion": read tcp 127.0.0.1:5434->127.0.0.1:5432: wsarecv: An existing connection was forcibly closed by the remote host. C:\Windows\SysWOW64> ### Relevant log output ```shell 2025/03/18 22:55:25 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\Oleg\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-03-18T22:55:25.261+03:00 level=INFO source=images.go:432 msg="total blobs: 0" time=2025-03-18T22:55:25.261+03:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0" time=2025-03-18T22:55:25.261+03:00 level=INFO source=routes.go:1297 msg="Listening on 127.0.0.1:11434 (version 0.6.2)" time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-03-18T22:55:25.262+03:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=6 efficiency=0 threads=12 time=2025-03-18T22:55:25.414+03:00 level=INFO source=gpu.go:377 msg="no compatible GPUs were discovered" time=2025-03-18T22:55:25.414+03:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=cpu variant="" compute="" driver=0.0 name="" total="64.0 GiB" available="56.2 GiB" [GIN] 2025/03/18 - 23:01:18 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/03/18 - 23:01:18 | 404 | 1.0512ms | 127.0.0.1 | POST "/api/show" time=2025-03-18T23:01:19.012+03:00 level=INFO source=download.go:176 msg="downloading ff82381e2bea in 16 257 MB part(s)" time=2025-03-18T23:02:20.558+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 13 attempt 0 failed: unexpected EOF, retrying in 1s" time=2025-03-18T23:03:06.564+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 14 attempt 0 failed: unexpected EOF, retrying in 1s" time=2025-03-18T23:04:46.789+03:00 level=INFO source=download.go:294 msg="ff82381e2bea part 2 attempt 0 failed: unexpected EOF, retrying in 1s" time=2025-03-18T23:07:21.559+03:00 level=INFO source=download.go:176 msg="downloading 43070e2d4e53 in 1 11 KB part(s)" time=2025-03-18T23:07:22.951+03:00 level=INFO source=download.go:176 msg="downloading 491dfa501e59 in 1 801 B part(s)" time=2025-03-18T23:07:24.355+03:00 level=INFO source=download.go:176 msg="downloading ed11eda7790d in 1 30 B part(s)" time=2025-03-18T23:07:25.755+03:00 level=INFO source=download.go:176 msg="downloading 42347cd80dc8 in 1 485 B part(s)" [GIN] 2025/03/18 - 23:07:30 | 200 | 6m12s | 127.0.0.1 | POST "/api/pull" [GIN] 2025/03/18 - 23:07:30 | 200 | 7.5122ms | 127.0.0.1 | POST "/api/show" time=2025-03-18T23:07:30.463+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.4 GiB" free_swap="54.7 GiB" time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0 time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128 time=2025-03-18T23:07:30.463+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128 time=2025-03-18T23:07:30.463+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.4 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 llama_model_load: vocab only - skipping tensors time=2025-03-18T23:07:30.514+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 9906" time=2025-03-18T23:07:30.518+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-18T23:07:30.518+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-03-18T23:07:30.519+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-03-18T23:07:30.545+03:00 level=INFO source=runner.go:846 msg="starting go runner" load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll time=2025-03-18T23:07:30.592+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang) time=2025-03-18T23:07:30.593+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:9906" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 0 print_info: n_ctx_train = 32768 print_info: n_embd = 4096 print_info: n_layer = 32 print_info: n_head = 32 print_info: n_head_kv = 8 print_info: n_rot = 128 print_info: n_swa = 0 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 4 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-05 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 14336 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 0 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 32768 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 7B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: CPU model buffer size = 3922.02 MiB time=2025-03-18T23:07:30.770+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 1000000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1 llama_kv_cache_init: CPU KV buffer size = 1024.00 MiB llama_init_from_model: KV self size = 1024.00 MiB, K (f16): 512.00 MiB, V (f16): 512.00 MiB llama_init_from_model: CPU output buffer size = 0.56 MiB llama_init_from_model: CPU compute buffer size = 560.01 MiB llama_init_from_model: graph nodes = 1030 llama_init_from_model: graph splits = 1 time=2025-03-18T23:07:32.274+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.76 seconds" [GIN] 2025/03/18 - 23:07:32 | 200 | 1.8312845s | 127.0.0.1 | POST "/api/generate" C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed [GIN] 2025/03/18 - 23:10:03 | 200 | 11.2662ms | 127.0.0.1 | POST "/api/chat" time=2025-03-18T23:10:03.934+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" [GIN] 2025/03/18 - 23:14:48 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/03/18 - 23:14:48 | 404 | 512.2µs | 127.0.0.1 | POST "/api/show" [GIN] 2025/03/18 - 23:14:49 | 200 | 999.2685ms | 127.0.0.1 | POST "/api/pull" [GIN] 2025/03/18 - 23:14:49 | 200 | 13.5051ms | 127.0.0.1 | POST "/api/show" time=2025-03-18T23:14:49.699+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.4 GiB" free_swap="54.8 GiB" time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0 time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128 time=2025-03-18T23:14:49.699+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128 time=2025-03-18T23:14:49.700+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.4 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 llama_model_load: vocab only - skipping tensors time=2025-03-18T23:14:49.744+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 5422" time=2025-03-18T23:14:49.748+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-18T23:14:49.748+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-03-18T23:14:49.748+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-03-18T23:14:49.782+03:00 level=INFO source=runner.go:846 msg="starting go runner" load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll time=2025-03-18T23:14:49.828+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang) time=2025-03-18T23:14:49.829+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:5422" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 0 print_info: n_ctx_train = 32768 print_info: n_embd = 4096 print_info: n_layer = 32 print_info: n_head = 32 print_info: n_head_kv = 8 print_info: n_rot = 128 print_info: n_swa = 0 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 4 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-05 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 14336 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 0 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 32768 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 7B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: CPU model buffer size = 3922.02 MiB time=2025-03-18T23:14:50.000+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 1000000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1 llama_kv_cache_init: CPU KV buffer size = 1024.00 MiB llama_init_from_model: KV self size = 1024.00 MiB, K (f16): 512.00 MiB, V (f16): 512.00 MiB llama_init_from_model: CPU output buffer size = 0.56 MiB llama_init_from_model: CPU compute buffer size = 560.01 MiB llama_init_from_model: graph nodes = 1030 llama_init_from_model: graph splits = 1 time=2025-03-18T23:14:51.503+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.75 seconds" [GIN] 2025/03/18 - 23:14:51 | 200 | 1.8278445s | 127.0.0.1 | POST "/api/generate" C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed [GIN] 2025/03/18 - 23:15:16 | 200 | 11.1082ms | 127.0.0.1 | POST "/api/chat" time=2025-03-18T23:15:16.613+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" [GIN] 2025/03/18 - 23:15:45 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/03/18 - 23:15:45 | 200 | 8.2655ms | 127.0.0.1 | POST "/api/show" time=2025-03-18T23:15:45.304+03:00 level=INFO source=server.go:105 msg="system memory" total="64.0 GiB" free="56.3 GiB" free_swap="54.7 GiB" time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.vision.block_count default=0 time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.key_length default=128 time=2025-03-18T23:15:45.304+03:00 level=WARN source=ggml.go:149 msg="key not found" key=llama.attention.value_length default=128 time=2025-03-18T23:15:45.304+03:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=33 layers.offload=0 layers.split="" memory.available="[56.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="5.5 GiB" memory.required.partial="0 B" memory.required.kv="1.0 GiB" memory.required.allocations="[5.5 GiB]" memory.weights.total="3.7 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="105.0 MiB" memory.graph.full="560.0 MiB" memory.graph.partial="585.0 MiB" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 llama_model_load: vocab only - skipping tensors time=2025-03-18T23:15:45.351+03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Oleg\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\Oleg\\.ollama\\models\\blobs\\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 --ctx-size 8192 --batch-size 512 --threads 6 --no-mmap --parallel 4 --port 5432" time=2025-03-18T23:15:45.355+03:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-18T23:15:45.355+03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-03-18T23:15:45.355+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-03-18T23:15:45.382+03:00 level=INFO source=runner.go:846 msg="starting go runner" load_backend: loaded CPU backend from C:\Users\Oleg\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll time=2025-03-18T23:15:45.426+03:00 level=INFO source=ggml.go:109 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.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang) time=2025-03-18T23:15:45.427+03:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:5432" llama_model_loader: loaded meta data with 25 key-value pairs and 291 tensors from C:\Users\Oleg\.ollama\models\blobs\sha256-ff82381e2bea77d91c1b824c7afb83f6fb73e9f7de9dda631bcdbca564aa5435 (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 = llama llama_model_loader: - kv 1: general.name str = Mistral-7B-Instruct-v0.3 llama_model_loader: - kv 2: llama.block_count u32 = 32 llama_model_loader: - kv 3: llama.context_length u32 = 32768 llama_model_loader: - kv 4: llama.embedding_length u32 = 4096 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.attention.head_count u32 = 32 llama_model_loader: - kv 7: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: general.file_type u32 = 2 llama_model_loader: - kv 11: llama.vocab_size u32 = 32768 llama_model_loader: - kv 12: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 13: tokenizer.ggml.model str = llama llama_model_loader: - kv 14: tokenizer.ggml.pre str = default llama_model_loader: - kv 15: tokenizer.ggml.tokens arr[str,32768] = ["<unk>", "<s>", "</s>", "[INST]", "[... llama_model_loader: - kv 16: tokenizer.ggml.scores arr[f32,32768] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 17: tokenizer.ggml.token_type arr[i32,32768] = [2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 21: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 22: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 23: tokenizer.chat_template str = {{ bos_token }}{% for message in mess... llama_model_loader: - kv 24: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_0 print_info: file size = 3.83 GiB (4.54 BPW) load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 771 load: token to piece cache size = 0.1731 MB print_info: arch = llama print_info: vocab_only = 0 print_info: n_ctx_train = 32768 print_info: n_embd = 4096 print_info: n_layer = 32 print_info: n_head = 32 print_info: n_head_kv = 8 print_info: n_rot = 128 print_info: n_swa = 0 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 4 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-05 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 14336 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 0 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 32768 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 7B print_info: model params = 7.25 B print_info: general.name = Mistral-7B-Instruct-v0.3 print_info: vocab type = SPM print_info: n_vocab = 32768 print_info: n_merges = 0 print_info: BOS token = 1 '<s>' print_info: EOS token = 2 '</s>' print_info: UNK token = 0 '<unk>' print_info: LF token = 781 '<0x0A>' print_info: EOG token = 2 '</s>' print_info: max token length = 48 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: CPU model buffer size = 3922.02 MiB time=2025-03-18T23:15:45.606+03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 1000000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 32, can_shift = 1 llama_kv_cache_init: CPU KV buffer size = 1024.00 MiB llama_init_from_model: KV self size = 1024.00 MiB, K (f16): 512.00 MiB, V (f16): 512.00 MiB llama_init_from_model: CPU output buffer size = 0.56 MiB llama_init_from_model: CPU compute buffer size = 560.01 MiB llama_init_from_model: graph nodes = 1030 llama_init_from_model: graph splits = 1 time=2025-03-18T23:15:47.109+03:00 level=INFO source=server.go:619 msg="llama runner started in 1.75 seconds" [GIN] 2025/03/18 - 23:15:47 | 200 | 1.82761s | 127.0.0.1 | POST "/api/generate" C:\For_AI\llama.cpp\ggml\src\ggml.c:1725: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed [GIN] 2025/03/18 - 23:16:27 | 200 | 10.8311ms | 127.0.0.1 | POST "/api/chat" time=2025-03-18T23:16:27.219+03:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" [GIN] 2025/03/18 - 23:21:43 | 200 | 0s | 127.0.0.1 | GET "/api/version" ``` ### OS Windows ### GPU AMD ### CPU AMD ### Ollama version 0.6.2

GiteaMirror added the bug label 2026-04-22 13:16:59 -05:00

GiteaMirror closed this issue

2026-04-22 13:16:59 -05:00

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pdevine/authorizedkeys

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parth/opt-in-error-context-window

brucemacd/cache-models

brucemacd/runner-completion

jmorganca/llama-update-6

brucemacd/benchmark-list

brucemacd/partial-read-caps

parth/deepseek-r1-tools

mxyng/omit-array

parth/tool-prefix-temp

brucemacd/runner-test

jmorganca/qwen25vl

brucemacd/model-forward-test-ext

parth/python-function-parsing

jmorganca/cuda-compression-none

drifkin/num-parallel

drifkin/chat-truncation-fix

jmorganca/sync

parth/python-tools-calling

drifkin/array-head-count

brucemacd/create-no-loop

parth/server-enable-content-stream-with-tools

qwen25omni

mxyng/v3

brucemacd/ropeconfig

jmorganca/silence-tokenizer

parth/sample-so-test

parth/sampling-structured-outputs

brucemacd/doc-go-engine

parth/constrained-sampling-json

jmorganca/mistral-wip

brucemacd/mistral-small-convert

parth/sample-unmarshal-json-for-params

brucemacd/jomorganca/mistral

pdevine/bfloat16

jmorganca/mistral

brucemacd/mistral

pdevine/logging

parth/sample-correctness-fix

parth/sample-fix-sorting

jmorgan/sample-fix-sorting-extras

jmorganca/temp-0-images

brucemacd/parallel-embed-models

brucemacd/shim-grammar

jmorganca/fix-gguf-error

bmizerany/nameswork

jmorganca/faster-releases

bmizerany/validatenames

brucemacd/err-no-vocab

brucemacd/rope-config

brucemacd/err-hint

brucemacd/qwen2_5

brucemacd/logprobs

brucemacd/new_runner_graph_bench

progress-flicker

brucemacd/forward-test

brucemacd/go_qwen2

pdevine/gemma2

jmorganca/add-missing-symlink-eval

mxyng/next-debug

parth/set-context-size-openai

brucemacd/next-bpe-bench

brucemacd/next-bpe-test

brucemacd/new_runner_e2e

brucemacd/new_runner_qwen2

pdevine/convert-cohere2

brucemacd/convert-cli

parth/log-probs

mxyng/next-mlx

mxyng/cmd-history

parth/templating

parth/tokenize-detokenize

brucemacd/check-key-register

bmizerany/grammar

jmorganca/vendor-081b29bd

mxyng/func-checks

jmorganca/fix-null-format

parth/fix-default-to-warn-json

jmorganca/qwen2vl

jmorganca/no-concat

parth/cmd-cleanup-SO

brucemacd/check-key-register-structured-err

parth/openai-stream-usage

parth/fix-referencing-so

stream-tools-stop

jmorganca/degin-1

brucemacd/install-path-clean

brucemacd/push-name-validation

brucemacd/browser-key-register

jmorganca/openai-fix-first-message

jmorganca/fix-proxy

jessegross/sample

parth/disallow-streaming-tools

dhiltgen/remove_submodule

jmorganca/ga

jmorganca/mllama

pdevine/newlines

pdevine/geems-2b

jmorganca/llama-bump

mxyng/modelname-7

mxyng/gin-slog

mxyng/modelname-6

jyan/convert-prog

jyan/quant5

paligemma-support

pdevine/import-docs

jmorganca/openai-context

jyan/paligemma

jyan/p2

jyan/palitest

bmizerany/embedspeedup

jmorganca/llama-vit

brucemacd/allow-ollama

royh/ep-methods

royh/whisper

mxyng/api-models

mxyng/fix-memory

jyan/q4_4/8

jyan/ollama-v

royh/stream-tools

roy-embed-parallel

bmizerany/hrm

revert-5963-revert-5924-mxyng/llama3.1-rope

royh/embed-viz

jyan/local2

jyan/auth

jyan/local

jyan/parse-temp

jmorganca/template-mistral

jyan/reord-g

royh-openai-suffixdocs

royh-imgembed

royh-embed-parallel

jyan/quant4

royh-precision

jyan/progress

pdevine/fix-template

jyan/quant3

pdevine/ggla

mxyng/update-registry-domain

jmorganca/ggml-static

mxyng/create-context

jyan/v0.146

mxyng/layers-from-files

build_dist

bmizerany/noseek

royh-ls

royh-name

timeout

mxyng/server-timestamp

bmizerany/nosillyggufslurps

royh-params

jmorganca/llama-cpp-7c26775

royh-openai-delete

royh-show-rigid

jmorganca/enable-fa

jmorganca/no-error-template

jyan/format

royh-testdelete

bmizerany/fastverify

language_support

pdevine/ps-glitches

brucemacd/tokenize

bruce/iq-quants

bmizerany/filepathwithcoloninhost

mxyng/split-bin

bmizerany/client-registry

jmorganca/if-none-match

native

jmorganca/native

jmorganca/batch-embeddings

jmorganca/initcmake

jmorganca/mm

pdevine/showggmlinfo

modenameenforcealphanum

bmizerany/modenameenforcealphanum

jmorganca/done-reason

jmorganca/llama-cpp-8960fe8

ollama.com

bmizerany/filepathnobuild

bmizerany/types/model/defaultfix

rmdisplaylong

nogogen

bmizerany/x

modelfile-readme

bmizerany/replacecolon

jmorganca/limit

jmorganca/execstack

jmorganca/replace-assets

mxyng/tune-concurrency

jmorganca/testing

whitespace-detection

jmorganca/options

upgrade-all

scratch

cuda-search

mattw/airenamer

mattw/allmodelsonhuggingface

mattw/quantcontext

mattw/whatneedstorun

brucemacd/llama-mem-calc

mattw/faq-context

mattw/communitylinks

mattw/noprune

mattw/python-functioncalling

rename

mxyng/install

pulse

remove-first

editor

mattw/selfqueryingretrieval

cgo

mattw/howtoquant

api

matt/streamingapi

format-config

mxyng/extra-args

shell

update-nous-hermes

cp-model

upload-progress

fix-unknown-model

fix-model-names

delete-fix

insecure-registry

ls

deletemodels

progressbar

readme-updates

license-layers

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list-models

modelpath

matt/examplemodelfiles

distribution

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Reference: github-starred/ollama#32223