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[GH-ISSUE #9091] Ollama 0.5.10 degree model performance for qwen models #31675

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opened 2026-04-22 12:21:59 -05:00 by GiteaMirror · 11 comments
GiteaMirror commented 2026-04-22 12:21:59 -05:00
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Originally created by @ice6 on GitHub (Feb 14, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9091

What is the issue?

after upgrading to Ollama 0.5.10 from 0.5.7, qwen model's start to talk wildly.

Relevant log output

OS

Windows

GPU

Nvidia

CPU

AMD

Ollama version

0.5.10

Originally created by @ice6 on GitHub (Feb 14, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9091 ### What is the issue? after upgrading to `Ollama 0.5.10` from 0.5.7, qwen model's start to talk wildly. ### Relevant log output ```shell ``` ### OS Windows ### GPU Nvidia ### CPU AMD ### Ollama version 0.5.10
GiteaMirror added the bug label 2026-04-22 12:21:59 -05:00
GiteaMirror commented 2026-04-22 12:22:04 -05:00
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@jmorganca commented on GitHub (Feb 14, 2025):

Hi there, may I ask which Qwen model you ran?

<!-- gh-comment-id:2658476750 --> @jmorganca commented on GitHub (Feb 14, 2025): Hi there, may I ask which Qwen model you ran?
GiteaMirror commented 2026-04-22 12:22:06 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

qwen2.5:14b and qwen2.5:32b.

<!-- gh-comment-id:2658491049 --> @ice6 commented on GitHub (Feb 14, 2025): `qwen2.5:14b` and `qwen2.5:32b`.
GiteaMirror commented 2026-04-22 12:22:09 -05:00
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@jmorganca commented on GitHub (Feb 14, 2025):

Thanks! @ice6 which GPU are you using?

<!-- gh-comment-id:2658509575 --> @jmorganca commented on GitHub (Feb 14, 2025): Thanks! @ice6 which GPU are you using?
GiteaMirror commented 2026-04-22 12:22:12 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

NVIDIA Geforce RTX 4090 / AMD Ryzen 9 5950x 16-Core Processor / 128G RAM / Win11

<!-- gh-comment-id:2658512035 --> @ice6 commented on GitHub (Feb 14, 2025): NVIDIA Geforce RTX 4090 / AMD Ryzen 9 5950x 16-Core Processor / 128G RAM / Win11
GiteaMirror commented 2026-04-22 12:22:12 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

@jmorganca I have downgrade to 0.5.7, everything works well now. I have not test other models, because in my app, these two models work best(better the deepseek-r1 14b/32b)

If you need more information, tell me what to do can help.

<!-- gh-comment-id:2658513021 --> @ice6 commented on GitHub (Feb 14, 2025): @jmorganca I have downgrade to `0.5.7`, everything works well now. I have not test other models, because in my app, these two models work best(better the deepseek-r1 14b/32b) If you need more information, tell me what to do can help.
GiteaMirror commented 2026-04-22 12:22:13 -05:00
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@jmorganca commented on GitHub (Feb 14, 2025):

Thanks @ice6, do you have the server logs? You can see them by clicking on Ollama -> View logs.

<!-- gh-comment-id:2658534673 --> @jmorganca commented on GitHub (Feb 14, 2025): Thanks @ice6, do you have the server logs? You can see them by clicking on Ollama -> View logs.
GiteaMirror commented 2026-04-22 12:22:13 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

OK, let me upgrade again. I will uninstall 0.5.7 and reinstall 0.5.10. so the 0.5.7 and 0.5.10's log is refresh.

<!-- gh-comment-id:2658537227 --> @ice6 commented on GitHub (Feb 14, 2025): OK, let me upgrade again. I will uninstall `0.5.7` and reinstall `0.5.10`. so the `0.5.7` and `0.5.10`'s log is refresh.
GiteaMirror commented 2026-04-22 12:22:14 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

this is 0.5.7 server log:

2025/02/14 15:46:16 routes.go:1187: 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_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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:D:\\.ollama\\models OLLAMA_MULTIUSER_CACHE: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://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-02-14T15:46:16.504+08:00 level=INFO source=images.go:432 msg="total blobs: 77"
time=2025-02-14T15:46:16.506+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0"
time=2025-02-14T15:46:16.507+08:00 level=INFO source=routes.go:1238 msg="Listening on [::]:11434 (version 0.5.7)"
time=2025-02-14T15:46:16.508+08:00 level=INFO source=routes.go:1267 msg="Dynamic LLM libraries" runners="[cpu_avx cpu_avx2 cuda_v11_avx cuda_v12_avx rocm_avx cpu]"
time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu.go:226 msg="looking for compatible GPUs"
time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32
time=2025-02-14T15:46:16.655+08:00 level=INFO source=types.go:131 msg="inference compute" id=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda variant=v12 compute=8.9 driver=12.7 name="NVIDIA GeForce RTX 4090" total="24.0 GiB" available="22.5 GiB"
[GIN] 2025/02/14 - 15:46:41 | 200 |       522.4µs |       127.0.0.1 | GET      "/api/version"
[GIN] 2025/02/14 - 15:46:43 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2025/02/14 - 15:46:43 | 200 |     15.6464ms |       127.0.0.1 | POST     "/api/show"
time=2025-02-14T15:46:43.828+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23806914560 required="10.8 GiB"
time=2025-02-14T15:46:43.855+08:00 level=INFO source=server.go:104 msg="system memory" total="127.9 GiB" free="105.3 GiB" free_swap="121.7 GiB"
time=2025-02-14T15:46:43.855+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[22.2 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.8 GiB" memory.required.partial="10.8 GiB" memory.required.kv="1.5 GiB" memory.required.allocations="[10.8 GiB]" memory.weights.total="8.9 GiB" memory.weights.repeating="8.3 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB"
time=2025-02-14T15:46:43.861+08:00 level=INFO source=server.go:376 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\runners\\cuda_v12_avx\\ollama_llama_server.exe runner --model D:\\.ollama\\models\\blobs\\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 16 --no-mmap --parallel 4 --port 54703"
time=2025-02-14T15:46:44.033+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1
time=2025-02-14T15:46:44.033+08:00 level=INFO source=server.go:555 msg="waiting for llama runner to start responding"
time=2025-02-14T15:46:44.034+08:00 level=INFO source=server.go:589 msg="waiting for server to become available" status="llm server error"
time=2025-02-14T15:46:52.511+08:00 level=INFO source=runner.go:936 msg="starting go runner"
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
time=2025-02-14T15:46:52.545+08:00 level=INFO source=runner.go:937 msg=system info="CUDA : ARCHS = 600,610,620,700,720,750,800,860,870,890,900 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | LLAMAFILE = 1 | AARCH64_REPACK = 1 | cgo(clang)" threads=16
time=2025-02-14T15:46:52.546+08:00 level=INFO source=.:0 msg="Server listening on 127.0.0.1:54703"
time=2025-02-14T15:46:52.552+08:00 level=INFO source=server.go:589 msg="waiting for server to become available" status="llm server loading model"
llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free
llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 14B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 14B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-1...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 14B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-14B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 48
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 13824
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  241 tensors
llama_model_loader: - type q4_K:  289 tensors
llama_model_loader: - type q6_K:   49 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 5120
llm_load_print_meta: n_layer          = 48
llm_load_print_meta: n_head           = 40
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 5
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-06
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             = 13824
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 2
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 32768
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       = 14B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 14.77 B
llm_load_print_meta: model size       = 8.37 GiB (4.87 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 14B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: offloading 48 repeating layers to GPU
llm_load_tensors: offloading output layer to GPU
llm_load_tensors: offloaded 49/49 layers to GPU
llm_load_tensors:          CPU model buffer size =   417.66 MiB
llm_load_tensors:        CUDA0 model buffer size =  8148.38 MiB
llama_new_context_with_model: n_seq_max     = 4
llama_new_context_with_model: n_ctx         = 8192
llama_new_context_with_model: n_ctx_per_seq = 2048
llama_new_context_with_model: n_batch       = 2048
llama_new_context_with_model: n_ubatch      = 512
llama_new_context_with_model: flash_attn    = 0
llama_new_context_with_model: freq_base     = 1000000.0
llama_new_context_with_model: freq_scale    = 1
llama_new_context_with_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 = 48, can_shift = 1
llama_kv_cache_init:      CUDA0 KV buffer size =  1536.00 MiB
llama_new_context_with_model: KV self size  = 1536.00 MiB, K (f16):  768.00 MiB, V (f16):  768.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =     2.40 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =   696.00 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    26.01 MiB
llama_new_context_with_model: graph nodes  = 1686
llama_new_context_with_model: graph splits = 2
time=2025-02-14T15:46:54.305+08:00 level=INFO source=server.go:594 msg="llama runner started in 10.27 seconds"
[GIN] 2025/02/14 - 15:46:54 | 200 |   10.5257035s |       127.0.0.1 | POST     "/api/generate"
llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 14B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 14B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-1...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 14B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-14B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 48
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 13824
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  241 tensors
llama_model_loader: - type q4_K:  289 tensors
llama_model_loader: - type q6_K:   49 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
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     = 14.77 B
llm_load_print_meta: model size       = 8.37 GiB (4.87 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 14B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llama_model_load: vocab only - skipping tensors
[GIN] 2025/02/14 - 15:47:03 | 200 |    1.5911454s |       127.0.0.1 | POST     "/api/chat"
[GIN] 2025/02/14 - 15:47:09 | 200 |      3.5963ms |    192.168.1.14 | GET      "/api/tags"
[GIN] 2025/02/14 - 15:47:19 | 200 |    8.1273928s |    192.168.1.14 | POST     "/api/chat"
<!-- gh-comment-id:2658553763 --> @ice6 commented on GitHub (Feb 14, 2025): this is `0.5.7` server log: ``` 2025/02/14 15:46:16 routes.go:1187: 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_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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:D:\\.ollama\\models OLLAMA_MULTIUSER_CACHE: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://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-02-14T15:46:16.504+08:00 level=INFO source=images.go:432 msg="total blobs: 77" time=2025-02-14T15:46:16.506+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0" time=2025-02-14T15:46:16.507+08:00 level=INFO source=routes.go:1238 msg="Listening on [::]:11434 (version 0.5.7)" time=2025-02-14T15:46:16.508+08:00 level=INFO source=routes.go:1267 msg="Dynamic LLM libraries" runners="[cpu_avx cpu_avx2 cuda_v11_avx cuda_v12_avx rocm_avx cpu]" time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu.go:226 msg="looking for compatible GPUs" time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-02-14T15:46:16.508+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32 time=2025-02-14T15:46:16.655+08:00 level=INFO source=types.go:131 msg="inference compute" id=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda variant=v12 compute=8.9 driver=12.7 name="NVIDIA GeForce RTX 4090" total="24.0 GiB" available="22.5 GiB" [GIN] 2025/02/14 - 15:46:41 | 200 | 522.4µs | 127.0.0.1 | GET "/api/version" [GIN] 2025/02/14 - 15:46:43 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/02/14 - 15:46:43 | 200 | 15.6464ms | 127.0.0.1 | POST "/api/show" time=2025-02-14T15:46:43.828+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23806914560 required="10.8 GiB" time=2025-02-14T15:46:43.855+08:00 level=INFO source=server.go:104 msg="system memory" total="127.9 GiB" free="105.3 GiB" free_swap="121.7 GiB" time=2025-02-14T15:46:43.855+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[22.2 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.8 GiB" memory.required.partial="10.8 GiB" memory.required.kv="1.5 GiB" memory.required.allocations="[10.8 GiB]" memory.weights.total="8.9 GiB" memory.weights.repeating="8.3 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB" time=2025-02-14T15:46:43.861+08:00 level=INFO source=server.go:376 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\lib\\ollama\\runners\\cuda_v12_avx\\ollama_llama_server.exe runner --model D:\\.ollama\\models\\blobs\\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 16 --no-mmap --parallel 4 --port 54703" time=2025-02-14T15:46:44.033+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1 time=2025-02-14T15:46:44.033+08:00 level=INFO source=server.go:555 msg="waiting for llama runner to start responding" time=2025-02-14T15:46:44.034+08:00 level=INFO source=server.go:589 msg="waiting for server to become available" status="llm server error" time=2025-02-14T15:46:52.511+08:00 level=INFO source=runner.go:936 msg="starting go runner" ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes time=2025-02-14T15:46:52.545+08:00 level=INFO source=runner.go:937 msg=system info="CUDA : ARCHS = 600,610,620,700,720,750,800,860,870,890,900 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | LLAMAFILE = 1 | AARCH64_REPACK = 1 | cgo(clang)" threads=16 time=2025-02-14T15:46:52.546+08:00 level=INFO source=.:0 msg="Server listening on 127.0.0.1:54703" time=2025-02-14T15:46:52.552+08:00 level=INFO source=server.go:589 msg="waiting for server to become available" status="llm server loading model" llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 14B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 14B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-1... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 14B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-14B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 48 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 13824 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type q4_K: 289 tensors llama_model_loader: - type q6_K: 49 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 32768 llm_load_print_meta: n_embd = 5120 llm_load_print_meta: n_layer = 48 llm_load_print_meta: n_head = 40 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_swa = 0 llm_load_print_meta: n_embd_head_k = 128 llm_load_print_meta: n_embd_head_v = 128 llm_load_print_meta: n_gqa = 5 llm_load_print_meta: n_embd_k_gqa = 1024 llm_load_print_meta: n_embd_v_gqa = 1024 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-06 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 = 13824 llm_load_print_meta: n_expert = 0 llm_load_print_meta: n_expert_used = 0 llm_load_print_meta: causal attn = 1 llm_load_print_meta: pooling type = 0 llm_load_print_meta: rope type = 2 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 1000000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 32768 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 = 14B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 14.77 B llm_load_print_meta: model size = 8.37 GiB (4.87 BPW) llm_load_print_meta: general.name = Qwen2.5 14B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llm_load_tensors: offloading 48 repeating layers to GPU llm_load_tensors: offloading output layer to GPU llm_load_tensors: offloaded 49/49 layers to GPU llm_load_tensors: CPU model buffer size = 417.66 MiB llm_load_tensors: CUDA0 model buffer size = 8148.38 MiB llama_new_context_with_model: n_seq_max = 4 llama_new_context_with_model: n_ctx = 8192 llama_new_context_with_model: n_ctx_per_seq = 2048 llama_new_context_with_model: n_batch = 2048 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 1000000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_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 = 48, can_shift = 1 llama_kv_cache_init: CUDA0 KV buffer size = 1536.00 MiB llama_new_context_with_model: KV self size = 1536.00 MiB, K (f16): 768.00 MiB, V (f16): 768.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 2.40 MiB llama_new_context_with_model: CUDA0 compute buffer size = 696.00 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 26.01 MiB llama_new_context_with_model: graph nodes = 1686 llama_new_context_with_model: graph splits = 2 time=2025-02-14T15:46:54.305+08:00 level=INFO source=server.go:594 msg="llama runner started in 10.27 seconds" [GIN] 2025/02/14 - 15:46:54 | 200 | 10.5257035s | 127.0.0.1 | POST "/api/generate" llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 14B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 14B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-1... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 14B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-14B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 48 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 13824 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type q4_K: 289 tensors llama_model_loader: - type q6_K: 49 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 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 = 14.77 B llm_load_print_meta: model size = 8.37 GiB (4.87 BPW) llm_load_print_meta: general.name = Qwen2.5 14B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llama_model_load: vocab only - skipping tensors [GIN] 2025/02/14 - 15:47:03 | 200 | 1.5911454s | 127.0.0.1 | POST "/api/chat" [GIN] 2025/02/14 - 15:47:09 | 200 | 3.5963ms | 192.168.1.14 | GET "/api/tags" [GIN] 2025/02/14 - 15:47:19 | 200 | 8.1273928s | 192.168.1.14 | POST "/api/chat" ```
GiteaMirror commented 2026-04-22 12:22:15 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

this 0.5.10:

2025/02/14 16:11:12 routes.go:1186: 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_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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:D:\\.ollama\\models OLLAMA_MULTIUSER_CACHE: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://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-02-14T16:11:12.350+08:00 level=INFO source=images.go:432 msg="total blobs: 77"
time=2025-02-14T16:11:12.353+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0"
time=2025-02-14T16:11:12.354+08:00 level=INFO source=routes.go:1237 msg="Listening on [::]:11434 (version 0.5.10)"
time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32
time=2025-02-14T16:11:12.665+08:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda variant=v12 compute=8.9 driver=12.7 name="NVIDIA GeForce RTX 4090" total="24.0 GiB" available="22.5 GiB"
[GIN] 2025/02/14 - 16:11:39 | 200 |            0s |       127.0.0.1 | GET      "/api/version"
[GIN] 2025/02/14 - 16:11:57 | 200 |     46.0997ms |    192.168.1.14 | GET      "/api/tags"
time=2025-02-14T16:11:59.234+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23601774592 required="10.8 GiB"
time=2025-02-14T16:11:59.258+08:00 level=INFO source=server.go:100 msg="system memory" total="127.9 GiB" free="105.6 GiB" free_swap="121.5 GiB"
time=2025-02-14T16:11:59.258+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[22.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.8 GiB" memory.required.partial="10.8 GiB" memory.required.kv="1.5 GiB" memory.required.allocations="[10.8 GiB]" memory.weights.total="8.9 GiB" memory.weights.repeating="8.3 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB"
time=2025-02-14T16:11:59.265+08:00 level=INFO source=server.go:381 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\.ollama\\models\\blobs\\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 16 --no-mmap --parallel 4 --port 56280"
time=2025-02-14T16:11:59.321+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1
time=2025-02-14T16:11:59.321+08:00 level=INFO source=server.go:558 msg="waiting for llama runner to start responding"
time=2025-02-14T16:11:59.322+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server error"
time=2025-02-14T16:11:59.350+08:00 level=INFO source=runner.go:936 msg="starting go runner"
time=2025-02-14T16:11:59.353+08:00 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(clang)" threads=16
time=2025-02-14T16:11:59.353+08:00 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:56280"
time=2025-02-14T16:11:59.574+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server loading model"
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
load_backend: loaded CUDA backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll
load_backend: loaded CPU backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free
llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 14B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 14B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-1...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 14B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-14B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 48
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 13824
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  241 tensors
llama_model_loader: - type q4_K:  289 tensors
llama_model_loader: - type q6_K:   49 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 5120
llm_load_print_meta: n_layer          = 48
llm_load_print_meta: n_head           = 40
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 5
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-06
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             = 13824
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 2
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 32768
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       = 14B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 14.77 B
llm_load_print_meta: model size       = 8.37 GiB (4.87 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 14B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: offloading 48 repeating layers to GPU
llm_load_tensors: offloading output layer to GPU
llm_load_tensors: offloaded 49/49 layers to GPU
llm_load_tensors:        CUDA0 model buffer size =  8148.38 MiB
llm_load_tensors:          CPU model buffer size =   417.66 MiB
llama_new_context_with_model: n_seq_max     = 4
llama_new_context_with_model: n_ctx         = 8192
llama_new_context_with_model: n_ctx_per_seq = 2048
llama_new_context_with_model: n_batch       = 2048
llama_new_context_with_model: n_ubatch      = 512
llama_new_context_with_model: flash_attn    = 0
llama_new_context_with_model: freq_base     = 1000000.0
llama_new_context_with_model: freq_scale    = 1
llama_new_context_with_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 = 48, can_shift = 1
llama_kv_cache_init:      CUDA0 KV buffer size =  1536.00 MiB
llama_new_context_with_model: KV self size  = 1536.00 MiB, K (f16):  768.00 MiB, V (f16):  768.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =     2.40 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =   696.00 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    26.01 MiB
llama_new_context_with_model: graph nodes  = 1686
llama_new_context_with_model: graph splits = 2
time=2025-02-14T16:12:01.828+08:00 level=INFO source=server.go:597 msg="llama runner started in 2.51 seconds"
llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 14B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 14B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-1...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 14B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-14B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 48
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 13824
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  241 tensors
llama_model_loader: - type q4_K:  289 tensors
llama_model_loader: - type q6_K:   49 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
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     = 14.77 B
llm_load_print_meta: model size       = 8.37 GiB (4.87 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 14B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llama_model_load: vocab only - skipping tensors
[GIN] 2025/02/14 - 16:12:09 | 200 |   10.5310793s |    192.168.1.14 | POST     "/api/chat"
[GIN] 2025/02/14 - 16:12:26 | 200 |            0s |       127.0.0.1 | GET      "/api/version"
[GIN] 2025/02/14 - 16:12:27 | 200 |            0s |       127.0.0.1 | GET      "/api/version"
[GIN] 2025/02/14 - 16:12:28 | 200 |            0s |       127.0.0.1 | HEAD     "/"
[GIN] 2025/02/14 - 16:12:28 | 200 |     15.1598ms |       127.0.0.1 | POST     "/api/show"
[GIN] 2025/02/14 - 16:12:29 | 200 |     14.4983ms |       127.0.0.1 | POST     "/api/generate"
[GIN] 2025/02/14 - 16:12:44 | 200 |      3.0963ms |    192.168.1.14 | GET      "/api/tags"
[GIN] 2025/02/14 - 16:12:57 | 200 |    7.3938854s |    192.168.1.14 | POST     "/api/chat"
time=2025-02-14T16:13:08.951+08:00 level=INFO source=sched.go:507 msg="updated VRAM based on existing loaded models" gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda total="24.0 GiB" available="11.4 GiB"
time=2025-02-14T16:13:09.282+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23604215808 required="21.5 GiB"
time=2025-02-14T16:13:09.303+08:00 level=INFO source=server.go:100 msg="system memory" total="127.9 GiB" free="105.9 GiB" free_swap="121.5 GiB"
time=2025-02-14T16:13:09.304+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=65 layers.offload=65 layers.split="" memory.available="[22.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="21.5 GiB" memory.required.partial="21.5 GiB" memory.required.kv="2.0 GiB" memory.required.allocations="[21.5 GiB]" memory.weights.total="19.5 GiB" memory.weights.repeating="18.9 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB"
time=2025-02-14T16:13:09.308+08:00 level=INFO source=server.go:381 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\.ollama\\models\\blobs\\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 --ctx-size 8192 --batch-size 512 --n-gpu-layers 65 --threads 16 --no-mmap --parallel 4 --port 56357"
time=2025-02-14T16:13:09.363+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1
time=2025-02-14T16:13:09.363+08:00 level=INFO source=server.go:558 msg="waiting for llama runner to start responding"
time=2025-02-14T16:13:09.363+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server error"
time=2025-02-14T16:13:09.392+08:00 level=INFO source=runner.go:936 msg="starting go runner"
time=2025-02-14T16:13:09.401+08:00 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(clang)" threads=16
time=2025-02-14T16:13:09.401+08:00 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:56357"
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
load_backend: loaded CUDA backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll
load_backend: loaded CPU backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
time=2025-02-14T16:13:09.614+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server loading model"
llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free
llama_model_loader: loaded meta data with 34 key-value pairs and 771 tensors from D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 32B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 32B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-3...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 32B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-32B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 64
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 27648
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  321 tensors
llama_model_loader: - type q4_K:  385 tensors
llama_model_loader: - type q6_K:   65 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
llm_load_print_meta: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 5120
llm_load_print_meta: n_layer          = 64
llm_load_print_meta: n_head           = 40
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_swa            = 0
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 5
llm_load_print_meta: n_embd_k_gqa     = 1024
llm_load_print_meta: n_embd_v_gqa     = 1024
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-06
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             = 27648
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 2
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn  = 32768
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       = 32B
llm_load_print_meta: model ftype      = Q4_K - Medium
llm_load_print_meta: model params     = 32.76 B
llm_load_print_meta: model size       = 18.48 GiB (4.85 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 32B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llm_load_tensors: offloading 64 repeating layers to GPU
llm_load_tensors: offloading output layer to GPU
llm_load_tensors: offloaded 65/65 layers to GPU
llm_load_tensors:        CUDA0 model buffer size = 18508.35 MiB
llm_load_tensors:          CPU model buffer size =   417.66 MiB
llama_new_context_with_model: n_seq_max     = 4
llama_new_context_with_model: n_ctx         = 8192
llama_new_context_with_model: n_ctx_per_seq = 2048
llama_new_context_with_model: n_batch       = 2048
llama_new_context_with_model: n_ubatch      = 512
llama_new_context_with_model: flash_attn    = 0
llama_new_context_with_model: freq_base     = 1000000.0
llama_new_context_with_model: freq_scale    = 1
llama_new_context_with_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 = 64, can_shift = 1
llama_kv_cache_init:      CUDA0 KV buffer size =  2048.00 MiB
llama_new_context_with_model: KV self size  = 2048.00 MiB, K (f16): 1024.00 MiB, V (f16): 1024.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =     2.40 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =   696.00 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    26.01 MiB
llama_new_context_with_model: graph nodes  = 2246
llama_new_context_with_model: graph splits = 2
time=2025-02-14T16:13:12.368+08:00 level=INFO source=server.go:597 msg="llama runner started in 3.00 seconds"
llama_model_loader: loaded meta data with 34 key-value pairs and 771 tensors from D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 (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              = qwen2
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen2.5 32B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Qwen2.5
llama_model_loader: - kv   5:                         general.size_label str              = 32B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                       general.license.link str              = https://huggingface.co/Qwen/Qwen2.5-3...
llama_model_loader: - kv   8:                   general.base_model.count u32              = 1
llama_model_loader: - kv   9:                  general.base_model.0.name str              = Qwen2.5 32B
llama_model_loader: - kv  10:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  11:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen2.5-32B
llama_model_loader: - kv  12:                               general.tags arr[str,2]       = ["chat", "text-generation"]
llama_model_loader: - kv  13:                          general.languages arr[str,1]       = ["en"]
llama_model_loader: - kv  14:                          qwen2.block_count u32              = 64
llama_model_loader: - kv  15:                       qwen2.context_length u32              = 32768
llama_model_loader: - kv  16:                     qwen2.embedding_length u32              = 5120
llama_model_loader: - kv  17:                  qwen2.feed_forward_length u32              = 27648
llama_model_loader: - kv  18:                 qwen2.attention.head_count u32              = 40
llama_model_loader: - kv  19:              qwen2.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                       qwen2.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  21:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                          general.file_type u32              = 15
llama_model_loader: - kv  23:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  24:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  25:                      tokenizer.ggml.tokens arr[str,152064]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  26:                  tokenizer.ggml.token_type arr[i32,152064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  27:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  28:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  29:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  30:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  31:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  32:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  33:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:  321 tensors
llama_model_loader: - type q4_K:  385 tensors
llama_model_loader: - type q6_K:   65 tensors
llm_load_vocab: special tokens cache size = 22
llm_load_vocab: token to piece cache size = 0.9310 MB
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = qwen2
llm_load_print_meta: vocab type       = BPE
llm_load_print_meta: n_vocab          = 152064
llm_load_print_meta: n_merges         = 151387
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     = 32.76 B
llm_load_print_meta: model size       = 18.48 GiB (4.85 BPW) 
llm_load_print_meta: general.name     = Qwen2.5 32B Instruct
llm_load_print_meta: BOS token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOS token        = 151645 '<|im_end|>'
llm_load_print_meta: EOT token        = 151645 '<|im_end|>'
llm_load_print_meta: PAD token        = 151643 '<|endoftext|>'
llm_load_print_meta: LF token         = 148848 'ÄĬ'
llm_load_print_meta: FIM PRE token    = 151659 '<|fim_prefix|>'
llm_load_print_meta: FIM SUF token    = 151661 '<|fim_suffix|>'
llm_load_print_meta: FIM MID token    = 151660 '<|fim_middle|>'
llm_load_print_meta: FIM PAD token    = 151662 '<|fim_pad|>'
llm_load_print_meta: FIM REP token    = 151663 '<|repo_name|>'
llm_load_print_meta: FIM SEP token    = 151664 '<|file_sep|>'
llm_load_print_meta: EOG token        = 151643 '<|endoftext|>'
llm_load_print_meta: EOG token        = 151645 '<|im_end|>'
llm_load_print_meta: EOG token        = 151662 '<|fim_pad|>'
llm_load_print_meta: EOG token        = 151663 '<|repo_name|>'
llm_load_print_meta: EOG token        = 151664 '<|file_sep|>'
llm_load_print_meta: max token length = 256
llama_model_load: vocab only - skipping tensors
[GIN] 2025/02/14 - 16:13:27 | 200 |    18.170363s |    192.168.1.14 | POST     "/api/chat"
<!-- gh-comment-id:2658554339 --> @ice6 commented on GitHub (Feb 14, 2025): this `0.5.10`: ``` 2025/02/14 16:11:12 routes.go:1186: 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_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://0.0.0.0:11434 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:D:\\.ollama\\models OLLAMA_MULTIUSER_CACHE: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://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-02-14T16:11:12.350+08:00 level=INFO source=images.go:432 msg="total blobs: 77" time=2025-02-14T16:11:12.353+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0" time=2025-02-14T16:11:12.354+08:00 level=INFO source=routes.go:1237 msg="Listening on [::]:11434 (version 0.5.10)" time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-02-14T16:11:12.355+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=16 efficiency=0 threads=32 time=2025-02-14T16:11:12.665+08:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda variant=v12 compute=8.9 driver=12.7 name="NVIDIA GeForce RTX 4090" total="24.0 GiB" available="22.5 GiB" [GIN] 2025/02/14 - 16:11:39 | 200 | 0s | 127.0.0.1 | GET "/api/version" [GIN] 2025/02/14 - 16:11:57 | 200 | 46.0997ms | 192.168.1.14 | GET "/api/tags" time=2025-02-14T16:11:59.234+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23601774592 required="10.8 GiB" time=2025-02-14T16:11:59.258+08:00 level=INFO source=server.go:100 msg="system memory" total="127.9 GiB" free="105.6 GiB" free_swap="121.5 GiB" time=2025-02-14T16:11:59.258+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=49 layers.offload=49 layers.split="" memory.available="[22.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="10.8 GiB" memory.required.partial="10.8 GiB" memory.required.kv="1.5 GiB" memory.required.allocations="[10.8 GiB]" memory.weights.total="8.9 GiB" memory.weights.repeating="8.3 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB" time=2025-02-14T16:11:59.265+08:00 level=INFO source=server.go:381 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\.ollama\\models\\blobs\\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 --ctx-size 8192 --batch-size 512 --n-gpu-layers 49 --threads 16 --no-mmap --parallel 4 --port 56280" time=2025-02-14T16:11:59.321+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1 time=2025-02-14T16:11:59.321+08:00 level=INFO source=server.go:558 msg="waiting for llama runner to start responding" time=2025-02-14T16:11:59.322+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server error" time=2025-02-14T16:11:59.350+08:00 level=INFO source=runner.go:936 msg="starting go runner" time=2025-02-14T16:11:59.353+08:00 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(clang)" threads=16 time=2025-02-14T16:11:59.353+08:00 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:56280" time=2025-02-14T16:11:59.574+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server loading model" ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes load_backend: loaded CUDA backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll load_backend: loaded CPU backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 14B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 14B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-1... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 14B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-14B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 48 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 13824 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type q4_K: 289 tensors llama_model_loader: - type q6_K: 49 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 32768 llm_load_print_meta: n_embd = 5120 llm_load_print_meta: n_layer = 48 llm_load_print_meta: n_head = 40 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_swa = 0 llm_load_print_meta: n_embd_head_k = 128 llm_load_print_meta: n_embd_head_v = 128 llm_load_print_meta: n_gqa = 5 llm_load_print_meta: n_embd_k_gqa = 1024 llm_load_print_meta: n_embd_v_gqa = 1024 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-06 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 = 13824 llm_load_print_meta: n_expert = 0 llm_load_print_meta: n_expert_used = 0 llm_load_print_meta: causal attn = 1 llm_load_print_meta: pooling type = 0 llm_load_print_meta: rope type = 2 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 1000000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 32768 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 = 14B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 14.77 B llm_load_print_meta: model size = 8.37 GiB (4.87 BPW) llm_load_print_meta: general.name = Qwen2.5 14B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llm_load_tensors: offloading 48 repeating layers to GPU llm_load_tensors: offloading output layer to GPU llm_load_tensors: offloaded 49/49 layers to GPU llm_load_tensors: CUDA0 model buffer size = 8148.38 MiB llm_load_tensors: CPU model buffer size = 417.66 MiB llama_new_context_with_model: n_seq_max = 4 llama_new_context_with_model: n_ctx = 8192 llama_new_context_with_model: n_ctx_per_seq = 2048 llama_new_context_with_model: n_batch = 2048 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 1000000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_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 = 48, can_shift = 1 llama_kv_cache_init: CUDA0 KV buffer size = 1536.00 MiB llama_new_context_with_model: KV self size = 1536.00 MiB, K (f16): 768.00 MiB, V (f16): 768.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 2.40 MiB llama_new_context_with_model: CUDA0 compute buffer size = 696.00 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 26.01 MiB llama_new_context_with_model: graph nodes = 1686 llama_new_context_with_model: graph splits = 2 time=2025-02-14T16:12:01.828+08:00 level=INFO source=server.go:597 msg="llama runner started in 2.51 seconds" llama_model_loader: loaded meta data with 34 key-value pairs and 579 tensors from D:\.ollama\models\blobs\sha256-2049f5674b1e92b4464e5729975c9689fcfbf0b0e4443ccf10b5339f370f9a54 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 14B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 14B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-1... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 14B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-14B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 48 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 13824 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 241 tensors llama_model_loader: - type q4_K: 289 tensors llama_model_loader: - type q6_K: 49 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 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 = 14.77 B llm_load_print_meta: model size = 8.37 GiB (4.87 BPW) llm_load_print_meta: general.name = Qwen2.5 14B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llama_model_load: vocab only - skipping tensors [GIN] 2025/02/14 - 16:12:09 | 200 | 10.5310793s | 192.168.1.14 | POST "/api/chat" [GIN] 2025/02/14 - 16:12:26 | 200 | 0s | 127.0.0.1 | GET "/api/version" [GIN] 2025/02/14 - 16:12:27 | 200 | 0s | 127.0.0.1 | GET "/api/version" [GIN] 2025/02/14 - 16:12:28 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2025/02/14 - 16:12:28 | 200 | 15.1598ms | 127.0.0.1 | POST "/api/show" [GIN] 2025/02/14 - 16:12:29 | 200 | 14.4983ms | 127.0.0.1 | POST "/api/generate" [GIN] 2025/02/14 - 16:12:44 | 200 | 3.0963ms | 192.168.1.14 | GET "/api/tags" [GIN] 2025/02/14 - 16:12:57 | 200 | 7.3938854s | 192.168.1.14 | POST "/api/chat" time=2025-02-14T16:13:08.951+08:00 level=INFO source=sched.go:507 msg="updated VRAM based on existing loaded models" gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace library=cuda total="24.0 GiB" available="11.4 GiB" time=2025-02-14T16:13:09.282+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 gpu=GPU-8477654a-3470-85f8-c47f-3a9f25137ace parallel=4 available=23604215808 required="21.5 GiB" time=2025-02-14T16:13:09.303+08:00 level=INFO source=server.go:100 msg="system memory" total="127.9 GiB" free="105.9 GiB" free_swap="121.5 GiB" time=2025-02-14T16:13:09.304+08:00 level=INFO source=memory.go:356 msg="offload to cuda" layers.requested=-1 layers.model=65 layers.offload=65 layers.split="" memory.available="[22.0 GiB]" memory.gpu_overhead="0 B" memory.required.full="21.5 GiB" memory.required.partial="21.5 GiB" memory.required.kv="2.0 GiB" memory.required.allocations="[21.5 GiB]" memory.weights.total="19.5 GiB" memory.weights.repeating="18.9 GiB" memory.weights.nonrepeating="609.1 MiB" memory.graph.full="676.0 MiB" memory.graph.partial="916.1 MiB" time=2025-02-14T16:13:09.308+08:00 level=INFO source=server.go:381 msg="starting llama server" cmd="C:\\Users\\ice6\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\.ollama\\models\\blobs\\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 --ctx-size 8192 --batch-size 512 --n-gpu-layers 65 --threads 16 --no-mmap --parallel 4 --port 56357" time=2025-02-14T16:13:09.363+08:00 level=INFO source=sched.go:449 msg="loaded runners" count=1 time=2025-02-14T16:13:09.363+08:00 level=INFO source=server.go:558 msg="waiting for llama runner to start responding" time=2025-02-14T16:13:09.363+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server error" time=2025-02-14T16:13:09.392+08:00 level=INFO source=runner.go:936 msg="starting go runner" time=2025-02-14T16:13:09.401+08:00 level=INFO source=runner.go:937 msg=system info="CPU : LLAMAFILE = 1 | CPU : LLAMAFILE = 1 | cgo(clang)" threads=16 time=2025-02-14T16:13:09.401+08:00 level=INFO source=runner.go:995 msg="Server listening on 127.0.0.1:56357" ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes load_backend: loaded CUDA backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\cuda_v12\ggml-cuda.dll load_backend: loaded CPU backend from C:\Users\ice6\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll time=2025-02-14T16:13:09.614+08:00 level=INFO source=server.go:592 msg="waiting for server to become available" status="llm server loading model" llama_load_model_from_file: using device CUDA0 (NVIDIA GeForce RTX 4090) - 22994 MiB free llama_model_loader: loaded meta data with 34 key-value pairs and 771 tensors from D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 32B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 32B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-3... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 32B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-32B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 64 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 27648 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 321 tensors llama_model_loader: - type q4_K: 385 tensors llama_model_loader: - type q6_K: 65 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 32768 llm_load_print_meta: n_embd = 5120 llm_load_print_meta: n_layer = 64 llm_load_print_meta: n_head = 40 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_swa = 0 llm_load_print_meta: n_embd_head_k = 128 llm_load_print_meta: n_embd_head_v = 128 llm_load_print_meta: n_gqa = 5 llm_load_print_meta: n_embd_k_gqa = 1024 llm_load_print_meta: n_embd_v_gqa = 1024 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-06 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 = 27648 llm_load_print_meta: n_expert = 0 llm_load_print_meta: n_expert_used = 0 llm_load_print_meta: causal attn = 1 llm_load_print_meta: pooling type = 0 llm_load_print_meta: rope type = 2 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 1000000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 32768 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 = 32B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 32.76 B llm_load_print_meta: model size = 18.48 GiB (4.85 BPW) llm_load_print_meta: general.name = Qwen2.5 32B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llm_load_tensors: offloading 64 repeating layers to GPU llm_load_tensors: offloading output layer to GPU llm_load_tensors: offloaded 65/65 layers to GPU llm_load_tensors: CUDA0 model buffer size = 18508.35 MiB llm_load_tensors: CPU model buffer size = 417.66 MiB llama_new_context_with_model: n_seq_max = 4 llama_new_context_with_model: n_ctx = 8192 llama_new_context_with_model: n_ctx_per_seq = 2048 llama_new_context_with_model: n_batch = 2048 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 1000000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_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 = 64, can_shift = 1 llama_kv_cache_init: CUDA0 KV buffer size = 2048.00 MiB llama_new_context_with_model: KV self size = 2048.00 MiB, K (f16): 1024.00 MiB, V (f16): 1024.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 2.40 MiB llama_new_context_with_model: CUDA0 compute buffer size = 696.00 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 26.01 MiB llama_new_context_with_model: graph nodes = 2246 llama_new_context_with_model: graph splits = 2 time=2025-02-14T16:13:12.368+08:00 level=INFO source=server.go:597 msg="llama runner started in 3.00 seconds" llama_model_loader: loaded meta data with 34 key-value pairs and 771 tensors from D:\.ollama\models\blobs\sha256-eabc98a9bcbfce7fd70f3e07de599f8fda98120fefed5881934161ede8bd1a41 (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 = qwen2 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen2.5 32B Instruct llama_model_loader: - kv 3: general.finetune str = Instruct llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 32B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/Qwen/Qwen2.5-3... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 32B llama_model_loader: - kv 10: general.base_model.0.organization str = Qwen llama_model_loader: - kv 11: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen2.5-32B llama_model_loader: - kv 12: general.tags arr[str,2] = ["chat", "text-generation"] llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 64 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 5120 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 27648 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 40 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 20: qwen2.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 21: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 22: general.file_type u32 = 15 llama_model_loader: - kv 23: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 24: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 27: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 29: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 30: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 31: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 32: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 33: general.quantization_version u32 = 2 llama_model_loader: - type f32: 321 tensors llama_model_loader: - type q4_K: 385 tensors llama_model_loader: - type q6_K: 65 tensors llm_load_vocab: special tokens cache size = 22 llm_load_vocab: token to piece cache size = 0.9310 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = qwen2 llm_load_print_meta: vocab type = BPE llm_load_print_meta: n_vocab = 152064 llm_load_print_meta: n_merges = 151387 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 = 32.76 B llm_load_print_meta: model size = 18.48 GiB (4.85 BPW) llm_load_print_meta: general.name = Qwen2.5 32B Instruct llm_load_print_meta: BOS token = 151643 '<|endoftext|>' llm_load_print_meta: EOS token = 151645 '<|im_end|>' llm_load_print_meta: EOT token = 151645 '<|im_end|>' llm_load_print_meta: PAD token = 151643 '<|endoftext|>' llm_load_print_meta: LF token = 148848 'ÄĬ' llm_load_print_meta: FIM PRE token = 151659 '<|fim_prefix|>' llm_load_print_meta: FIM SUF token = 151661 '<|fim_suffix|>' llm_load_print_meta: FIM MID token = 151660 '<|fim_middle|>' llm_load_print_meta: FIM PAD token = 151662 '<|fim_pad|>' llm_load_print_meta: FIM REP token = 151663 '<|repo_name|>' llm_load_print_meta: FIM SEP token = 151664 '<|file_sep|>' llm_load_print_meta: EOG token = 151643 '<|endoftext|>' llm_load_print_meta: EOG token = 151645 '<|im_end|>' llm_load_print_meta: EOG token = 151662 '<|fim_pad|>' llm_load_print_meta: EOG token = 151663 '<|repo_name|>' llm_load_print_meta: EOG token = 151664 '<|file_sep|>' llm_load_print_meta: max token length = 256 llama_model_load: vocab only - skipping tensors [GIN] 2025/02/14 - 16:13:27 | 200 | 18.170363s | 192.168.1.14 | POST "/api/chat" ```
GiteaMirror commented 2026-04-22 12:22:16 -05:00
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@ice6 commented on GitHub (Feb 14, 2025):

@jmorganca after full reinstallation, it works now. so strange... feel free to close this issue.

<!-- gh-comment-id:2658558216 --> @ice6 commented on GitHub (Feb 14, 2025): @jmorganca after full reinstallation, it works now. so strange... feel free to close this issue.
GiteaMirror commented 2026-04-22 12:22:17 -05:00
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@jmorganca commented on GitHub (Feb 14, 2025):

@ice6 thanks for letting me know. Will keep an eye out for the issue again 🤔 . I really appreciate you sharing the logs, thank you!

<!-- gh-comment-id:2658567794 --> @jmorganca commented on GitHub (Feb 14, 2025): @ice6 thanks for letting me know. Will keep an eye out for the issue again 🤔 . I really appreciate you sharing the logs, thank you!
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