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[GH-ISSUE #9993] 不能聊天 #53060

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opened 2026-04-29 01:47:02 -05:00 by GiteaMirror · 2 comments
GiteaMirror commented 2026-04-29 01:47:02 -05:00
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Originally created by @bmb-li on GitHub (Mar 26, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9993

What is the issue?

PS C:\Users\Administrator> ollama run deepseek-r1:1.5b

123
Error: POST predict: Post "http://127.0.0.1:56327/completion": read tcp 127.0.0.1:56329->127.0.0.1:56327: wsarecv: An existing connection was forcibly closed by the remote host.

server-log:
2025/03/26 08:12:59 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://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:\Users\.ollama\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-03-26T08:12:59.824+08:00 level=INFO source=images.go:432 msg="total blobs: 28"
time=2025-03-26T08:12:59.827+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0"
time=2025-03-26T08:12:59.831+08:00 level=INFO source=routes.go:1297 msg="Listening on [::]:11434 (version 0.6.3-rc0)"
time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=4 efficiency=0 threads=4
time=2025-03-26T08:12:59.844+08:00 level=INFO source=gpu.go:612 msg="Unable to load cudart library C:\WINDOWS\system32\nvcuda.dll: symbol lookup for cuCtxCreate_v3 failed: \xd5Ҳ\xbb\xb5\xbdָ\xb6\xa8\xb5ij\xcc\xd0\xf2\xa1\xa3\r\n"
time=2025-03-26T08:12:59.945+08:00 level=INFO source=gpu.go:303 msg="[0] CUDA GPU is too old. Compute Capability detected: 3.0"
time=2025-03-26T08:12:59.947+08:00 level=INFO source=gpu.go:377 msg="no compatible GPUs were discovered"
time=2025-03-26T08:12:59.956+08:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=cpu variant="" compute="" driver=0.0 name="" total="7.9 GiB" available="5.0 GiB"
[GIN] 2025/03/26 - 08:13:58 | 200 | 4.0984ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:13:58 | 200 | 0s | 127.0.0.1 | GET "/"
[GIN] 2025/03/26 - 08:13:58 | 200 | 5.8591ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:14:05 | 200 | 3.5838ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:14:05 | 200 | 0s | 127.0.0.1 | GET "/"
[GIN] 2025/03/26 - 08:14:05 | 200 | 4.579ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:14:28 | 200 | 3.2282ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:14:28 | 200 | 0s | 127.0.0.1 | GET "/"
[GIN] 2025/03/26 - 08:14:28 | 200 | 5.3794ms | 127.0.0.1 | GET "/api/tags"
time=2025-03-26T08:14:55.177+08:00 level=INFO source=server.go:105 msg="system memory" total="7.9 GiB" free="4.9 GiB" free_swap="14.6 GiB"
time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.vision.block_count default=0
time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.key_length default=64
time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.value_length default=64
time=2025-03-26T08:14:55.177+08:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=25 layers.offload=0 layers.split="" memory.available="[4.9 GiB]" memory.gpu_overhead="0 B" memory.required.full="782.6 MiB" memory.required.partial="0 B" memory.required.kv="96.0 MiB" memory.required.allocations="[782.6 MiB]" memory.weights.total="235.8 MiB" memory.weights.repeating="235.8 MiB" memory.weights.nonrepeating="137.9 MiB" memory.graph.full="298.5 MiB" memory.graph.partial="405.0 MiB"
llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated
llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated
llama_model_loader: - kv 4: general.basename str = Qwen2.5
llama_model_loader: - kv 5: general.size_label str = 0.5B
llama_model_loader: - kv 6: general.license str = apache-2.0
llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen...
llama_model_loader: - kv 8: general.base_model.count u32 = 1
llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct
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/Qwen2.5-0...
llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",...
llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 14: qwen2.block_count u32 = 24
llama_model_loader: - kv 15: qwen2.context_length u32 = 32768
llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896
llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864
llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14
llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2
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,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors
llama_model_loader: - type q5_0: 132 tensors
llama_model_loader: - type q8_0: 13 tensors
llama_model_loader: - type q4_K: 12 tensors
llama_model_loader: - type q6_K: 12 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 373.71 MiB (6.35 BPW)
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch = qwen2
print_info: vocab_only = 1
print_info: model type = ?B
print_info: model params = 494.03 M
print_info: general.name = Qwen2.5 0.5B Instruct Abliterated
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2025-03-26T08:14:55.516+08:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\Users\Administrator\AppData\Local\Programs\Ollama\ollama.exe runner --model D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c --ctx-size 8192 --batch-size 512 --threads 4 --no-mmap --parallel 4 --port 54057"
time=2025-03-26T08:14:55.522+08:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-26T08:14:55.522+08:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-03-26T08:14:55.523+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-03-26T08:14:55.553+08:00 level=INFO source=runner.go:846 msg="starting go runner"
load_backend: loaded CPU backend from C:\Users\Administrator\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-sandybridge.dll
time=2025-03-26T08:14:55.603+08:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2025-03-26T08:14:55.605+08:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:54057"
llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated
llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated
llama_model_loader: - kv 4: general.basename str = Qwen2.5
llama_model_loader: - kv 5: general.size_label str = 0.5B
llama_model_loader: - kv 6: general.license str = apache-2.0
llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen...
llama_model_loader: - kv 8: general.base_model.count u32 = 1
llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct
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/Qwen2.5-0...
llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",...
llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 14: qwen2.block_count u32 = 24
llama_model_loader: - kv 15: qwen2.context_length u32 = 32768
llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896
llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864
llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14
llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2
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,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors
llama_model_loader: - type q5_0: 132 tensors
llama_model_loader: - type q8_0: 13 tensors
llama_model_loader: - type q4_K: 12 tensors
llama_model_loader: - type q6_K: 12 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 373.71 MiB (6.35 BPW)
time=2025-03-26T08:14:55.776+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch = qwen2
print_info: vocab_only = 0
print_info: n_ctx_train = 32768
print_info: n_embd = 896
print_info: n_layer = 24
print_info: n_head = 14
print_info: n_head_kv = 2
print_info: n_rot = 64
print_info: n_swa = 0
print_info: n_embd_head_k = 64
print_info: n_embd_head_v = 64
print_info: n_gqa = 7
print_info: n_embd_k_gqa = 128
print_info: n_embd_v_gqa = 128
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: n_ff = 4864
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 32768
print_info: rope_finetuned = unknown
print_info: ssm_d_conv = 0
print_info: ssm_d_inner = 0
print_info: ssm_d_state = 0
print_info: ssm_dt_rank = 0
print_info: ssm_dt_b_c_rms = 0
print_info: model type = 1B
print_info: model params = 494.03 M
print_info: general.name = Qwen2.5 0.5B Instruct Abliterated
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors: CPU model buffer size = 373.71 MiB
llama_init_from_model: n_seq_max = 4
llama_init_from_model: n_ctx = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch = 2048
llama_init_from_model: n_ubatch = 512
llama_init_from_model: flash_attn = 0
llama_init_from_model: freq_base = 1000000.0
llama_init_from_model: freq_scale = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 24, can_shift = 1
llama_kv_cache_init: CPU KV buffer size = 96.00 MiB
llama_init_from_model: KV self size = 96.00 MiB, K (f16): 48.00 MiB, V (f16): 48.00 MiB
llama_init_from_model: CPU output buffer size = 2.33 MiB
llama_init_from_model: CPU compute buffer size = 300.25 MiB
llama_init_from_model: graph nodes = 846
llama_init_from_model: graph splits = 1
time=2025-03-26T08:14:56.277+08:00 level=INFO source=server.go:619 msg="llama runner started in 0.75 seconds"
..\ggml\src\ggml.c:1721: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed
[GIN] 2025/03/26 - 08:14:56 | 200 | 1.3681925s | 127.0.0.1 | POST "/api/chat"
time=2025-03-26T08:14:56.524+08:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"
[GIN] 2025/03/26 - 08:16:11 | 200 | 3.9976ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:16:11 | 200 | 5.5846ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:16:42 | 200 | 3.2038ms | 127.0.0.1 | GET "/api/tags"
[GIN] 2025/03/26 - 08:16:42 | 200 | 0s | 127.0.0.1 | GET "/"
[GIN] 2025/03/26 - 08:16:42 | 200 | 6.2029ms | 127.0.0.1 | GET "/api/tags"
time=2025-03-26T08:16:48.085+08:00 level=INFO source=server.go:105 msg="system memory" total="7.9 GiB" free="4.5 GiB" free_swap="14.2 GiB"
time=2025-03-26T08:16:48.085+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.vision.block_count default=0
time=2025-03-26T08:16:48.086+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.key_length default=64
time=2025-03-26T08:16:48.086+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.value_length default=64
time=2025-03-26T08:16:48.086+08:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=25 layers.offload=0 layers.split="" memory.available="[4.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="782.6 MiB" memory.required.partial="0 B" memory.required.kv="96.0 MiB" memory.required.allocations="[782.6 MiB]" memory.weights.total="235.8 MiB" memory.weights.repeating="235.8 MiB" memory.weights.nonrepeating="137.9 MiB" memory.graph.full="298.5 MiB" memory.graph.partial="405.0 MiB"
llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated
llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated
llama_model_loader: - kv 4: general.basename str = Qwen2.5
llama_model_loader: - kv 5: general.size_label str = 0.5B
llama_model_loader: - kv 6: general.license str = apache-2.0
llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen...
llama_model_loader: - kv 8: general.base_model.count u32 = 1
llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct
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/Qwen2.5-0...
llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",...
llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 14: qwen2.block_count u32 = 24
llama_model_loader: - kv 15: qwen2.context_length u32 = 32768
llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896
llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864
llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14
llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2
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,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors
llama_model_loader: - type q5_0: 132 tensors
llama_model_loader: - type q8_0: 13 tensors
llama_model_loader: - type q4_K: 12 tensors
llama_model_loader: - type q6_K: 12 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 373.71 MiB (6.35 BPW)
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch = qwen2
print_info: vocab_only = 1
print_info: model type = ?B
print_info: model params = 494.03 M
print_info: general.name = Qwen2.5 0.5B Instruct Abliterated
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2025-03-26T08:16:48.414+08:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\Users\Administrator\AppData\Local\Programs\Ollama\ollama.exe runner --model D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c --ctx-size 8192 --batch-size 512 --threads 4 --no-mmap --parallel 4 --port 54138"
time=2025-03-26T08:16:48.419+08:00 level=INFO source=sched.go:450 msg="loaded runners" count=1
time=2025-03-26T08:16:48.419+08:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-03-26T08:16:48.419+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-03-26T08:16:48.459+08:00 level=INFO source=runner.go:846 msg="starting go runner"
load_backend: loaded CPU backend from C:\Users\Administrator\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-sandybridge.dll
time=2025-03-26T08:16:48.502+08:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang)
time=2025-03-26T08:16:48.504+08:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:54138"
llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated
llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated
llama_model_loader: - kv 4: general.basename str = Qwen2.5
llama_model_loader: - kv 5: general.size_label str = 0.5B
llama_model_loader: - kv 6: general.license str = apache-2.0
llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen...
llama_model_loader: - kv 8: general.base_model.count u32 = 1
llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct
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/Qwen2.5-0...
llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",...
llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 14: qwen2.block_count u32 = 24
llama_model_loader: - kv 15: qwen2.context_length u32 = 32768
llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896
llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864
llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14
llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2
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,151936] = ["!", """, "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors
llama_model_loader: - type q5_0: 132 tensors
llama_model_loader: - type q8_0: 13 tensors
llama_model_loader: - type q4_K: 12 tensors
llama_model_loader: - type q6_K: 12 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 373.71 MiB (6.35 BPW)
time=2025-03-26T08:16:48.671+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch = qwen2
print_info: vocab_only = 0
print_info: n_ctx_train = 32768
print_info: n_embd = 896
print_info: n_layer = 24
print_info: n_head = 14
print_info: n_head_kv = 2
print_info: n_rot = 64
print_info: n_swa = 0
print_info: n_embd_head_k = 64
print_info: n_embd_head_v = 64
print_info: n_gqa = 7
print_info: n_embd_k_gqa = 128
print_info: n_embd_v_gqa = 128
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: n_ff = 4864
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 32768
print_info: rope_finetuned = unknown
print_info: ssm_d_conv = 0
print_info: ssm_d_inner = 0
print_info: ssm_d_state = 0
print_info: ssm_dt_rank = 0
print_info: ssm_dt_b_c_rms = 0
print_info: model type = 1B
print_info: model params = 494.03 M
print_info: general.name = Qwen2.5 0.5B Instruct Abliterated
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 151643 '<|endoftext|>'
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151643 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors: CPU model buffer size = 373.71 MiB
llama_init_from_model: n_seq_max = 4
llama_init_from_model: n_ctx = 8192
llama_init_from_model: n_ctx_per_seq = 2048
llama_init_from_model: n_batch = 2048
llama_init_from_model: n_ubatch = 512
llama_init_from_model: flash_attn = 0
llama_init_from_model: freq_base = 1000000.0
llama_init_from_model: freq_scale = 1
llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 24, can_shift = 1
llama_kv_cache_init: CPU KV buffer size = 96.00 MiB
llama_init_from_model: KV self size = 96.00 MiB, K (f16): 48.00 MiB, V (f16): 48.00 MiB
llama_init_from_model: CPU output buffer size = 2.33 MiB
llama_init_from_model: CPU compute buffer size = 300.25 MiB
llama_init_from_model: graph nodes = 846
llama_init_from_model: graph splits = 1
time=2025-03-26T08:16:49.172+08:00 level=INFO source=server.go:619 msg="llama runner started in 0.75 seconds"
..\ggml\src\ggml.c:1721: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed
[GIN] 2025/03/26 - 08:16:49 | 200 | 1.287076s | 127.0.0.1 | POST "/api/chat"
time=2025-03-26T08:16:49.322+08:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409"

Relevant log output

OS

Windows

GPU

No response

CPU

Intel

Ollama version

0.6.3-rc0

Originally created by @bmb-li on GitHub (Mar 26, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9993 ### What is the issue? PS C:\Users\Administrator> ollama run deepseek-r1:1.5b >>> 123 Error: POST predict: Post "http://127.0.0.1:56327/completion": read tcp 127.0.0.1:56329->127.0.0.1:56327: wsarecv: An existing connection was forcibly closed by the remote host. server-log: 2025/03/26 08:12:59 routes.go:1230: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://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:\\Users\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-03-26T08:12:59.824+08:00 level=INFO source=images.go:432 msg="total blobs: 28" time=2025-03-26T08:12:59.827+08:00 level=INFO source=images.go:439 msg="total unused blobs removed: 0" time=2025-03-26T08:12:59.831+08:00 level=INFO source=routes.go:1297 msg="Listening on [::]:11434 (version 0.6.3-rc0)" time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-03-26T08:12:59.831+08:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=4 efficiency=0 threads=4 time=2025-03-26T08:12:59.844+08:00 level=INFO source=gpu.go:612 msg="Unable to load cudart library C:\\WINDOWS\\system32\\nvcuda.dll: symbol lookup for cuCtxCreate_v3 failed: \xd5Ҳ\xbb\xb5\xbdָ\xb6\xa8\xb5ij\xcc\xd0\xf2\xa1\xa3\r\n" time=2025-03-26T08:12:59.945+08:00 level=INFO source=gpu.go:303 msg="[0] CUDA GPU is too old. Compute Capability detected: 3.0" time=2025-03-26T08:12:59.947+08:00 level=INFO source=gpu.go:377 msg="no compatible GPUs were discovered" time=2025-03-26T08:12:59.956+08:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=cpu variant="" compute="" driver=0.0 name="" total="7.9 GiB" available="5.0 GiB" [GIN] 2025/03/26 - 08:13:58 | 200 | 4.0984ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:13:58 | 200 | 0s | 127.0.0.1 | GET "/" [GIN] 2025/03/26 - 08:13:58 | 200 | 5.8591ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:14:05 | 200 | 3.5838ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:14:05 | 200 | 0s | 127.0.0.1 | GET "/" [GIN] 2025/03/26 - 08:14:05 | 200 | 4.579ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:14:28 | 200 | 3.2282ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:14:28 | 200 | 0s | 127.0.0.1 | GET "/" [GIN] 2025/03/26 - 08:14:28 | 200 | 5.3794ms | 127.0.0.1 | GET "/api/tags" time=2025-03-26T08:14:55.177+08:00 level=INFO source=server.go:105 msg="system memory" total="7.9 GiB" free="4.9 GiB" free_swap="14.6 GiB" time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.vision.block_count default=0 time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.key_length default=64 time=2025-03-26T08:14:55.177+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.value_length default=64 time=2025-03-26T08:14:55.177+08:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=25 layers.offload=0 layers.split="" memory.available="[4.9 GiB]" memory.gpu_overhead="0 B" memory.required.full="782.6 MiB" memory.required.partial="0 B" memory.required.kv="96.0 MiB" memory.required.allocations="[782.6 MiB]" memory.weights.total="235.8 MiB" memory.weights.repeating="235.8 MiB" memory.weights.nonrepeating="137.9 MiB" memory.graph.full="298.5 MiB" memory.graph.partial="405.0 MiB" llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 0.5B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct 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/Qwen2.5-0... llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",... llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 24 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2 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,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors llama_model_loader: - type q5_0: 132 tensors llama_model_loader: - type q8_0: 13 tensors llama_model_loader: - type q4_K: 12 tensors llama_model_loader: - type q6_K: 12 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 373.71 MiB (6.35 BPW) load: special tokens cache size = 22 load: token to piece cache size = 0.9310 MB print_info: arch = qwen2 print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 494.03 M print_info: general.name = Qwen2.5 0.5B Instruct Abliterated print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 llama_model_load: vocab only - skipping tensors time=2025-03-26T08:14:55.516+08:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Administrator\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\Users\\.ollama\\models\\blobs\\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c --ctx-size 8192 --batch-size 512 --threads 4 --no-mmap --parallel 4 --port 54057" time=2025-03-26T08:14:55.522+08:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-26T08:14:55.522+08:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-03-26T08:14:55.523+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-03-26T08:14:55.553+08:00 level=INFO source=runner.go:846 msg="starting go runner" load_backend: loaded CPU backend from C:\Users\Administrator\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-sandybridge.dll time=2025-03-26T08:14:55.603+08:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang) time=2025-03-26T08:14:55.605+08:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:54057" llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 0.5B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct 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/Qwen2.5-0... llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",... llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 24 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2 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,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors llama_model_loader: - type q5_0: 132 tensors llama_model_loader: - type q8_0: 13 tensors llama_model_loader: - type q4_K: 12 tensors llama_model_loader: - type q6_K: 12 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 373.71 MiB (6.35 BPW) time=2025-03-26T08:14:55.776+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" load: special tokens cache size = 22 load: token to piece cache size = 0.9310 MB print_info: arch = qwen2 print_info: vocab_only = 0 print_info: n_ctx_train = 32768 print_info: n_embd = 896 print_info: n_layer = 24 print_info: n_head = 14 print_info: n_head_kv = 2 print_info: n_rot = 64 print_info: n_swa = 0 print_info: n_embd_head_k = 64 print_info: n_embd_head_v = 64 print_info: n_gqa = 7 print_info: n_embd_k_gqa = 128 print_info: n_embd_v_gqa = 128 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-06 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 4864 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 2 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 32768 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 1B print_info: model params = 494.03 M print_info: general.name = Qwen2.5 0.5B Instruct Abliterated print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: CPU model buffer size = 373.71 MiB llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 1000000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 24, can_shift = 1 llama_kv_cache_init: CPU KV buffer size = 96.00 MiB llama_init_from_model: KV self size = 96.00 MiB, K (f16): 48.00 MiB, V (f16): 48.00 MiB llama_init_from_model: CPU output buffer size = 2.33 MiB llama_init_from_model: CPU compute buffer size = 300.25 MiB llama_init_from_model: graph nodes = 846 llama_init_from_model: graph splits = 1 time=2025-03-26T08:14:56.277+08:00 level=INFO source=server.go:619 msg="llama runner started in 0.75 seconds" ..\ggml\src\ggml.c:1721: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed [GIN] 2025/03/26 - 08:14:56 | 200 | 1.3681925s | 127.0.0.1 | POST "/api/chat" time=2025-03-26T08:14:56.524+08:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" [GIN] 2025/03/26 - 08:16:11 | 200 | 3.9976ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:16:11 | 200 | 5.5846ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:16:42 | 200 | 3.2038ms | 127.0.0.1 | GET "/api/tags" [GIN] 2025/03/26 - 08:16:42 | 200 | 0s | 127.0.0.1 | GET "/" [GIN] 2025/03/26 - 08:16:42 | 200 | 6.2029ms | 127.0.0.1 | GET "/api/tags" time=2025-03-26T08:16:48.085+08:00 level=INFO source=server.go:105 msg="system memory" total="7.9 GiB" free="4.5 GiB" free_swap="14.2 GiB" time=2025-03-26T08:16:48.085+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.vision.block_count default=0 time=2025-03-26T08:16:48.086+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.key_length default=64 time=2025-03-26T08:16:48.086+08:00 level=WARN source=ggml.go:149 msg="key not found" key=qwen2.attention.value_length default=64 time=2025-03-26T08:16:48.086+08:00 level=INFO source=server.go:138 msg=offload library=cpu layers.requested=-1 layers.model=25 layers.offload=0 layers.split="" memory.available="[4.5 GiB]" memory.gpu_overhead="0 B" memory.required.full="782.6 MiB" memory.required.partial="0 B" memory.required.kv="96.0 MiB" memory.required.allocations="[782.6 MiB]" memory.weights.total="235.8 MiB" memory.weights.repeating="235.8 MiB" memory.weights.nonrepeating="137.9 MiB" memory.graph.full="298.5 MiB" memory.graph.partial="405.0 MiB" llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 0.5B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct 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/Qwen2.5-0... llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",... llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 24 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2 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,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors llama_model_loader: - type q5_0: 132 tensors llama_model_loader: - type q8_0: 13 tensors llama_model_loader: - type q4_K: 12 tensors llama_model_loader: - type q6_K: 12 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 373.71 MiB (6.35 BPW) load: special tokens cache size = 22 load: token to piece cache size = 0.9310 MB print_info: arch = qwen2 print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 494.03 M print_info: general.name = Qwen2.5 0.5B Instruct Abliterated print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 llama_model_load: vocab only - skipping tensors time=2025-03-26T08:16:48.414+08:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\Administrator\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model D:\\Users\\.ollama\\models\\blobs\\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c --ctx-size 8192 --batch-size 512 --threads 4 --no-mmap --parallel 4 --port 54138" time=2025-03-26T08:16:48.419+08:00 level=INFO source=sched.go:450 msg="loaded runners" count=1 time=2025-03-26T08:16:48.419+08:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-03-26T08:16:48.419+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-03-26T08:16:48.459+08:00 level=INFO source=runner.go:846 msg="starting go runner" load_backend: loaded CPU backend from C:\Users\Administrator\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-sandybridge.dll time=2025-03-26T08:16:48.502+08:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 compiler=cgo(clang) time=2025-03-26T08:16:48.504+08:00 level=INFO source=runner.go:906 msg="Server listening on 127.0.0.1:54138" llama_model_loader: loaded meta data with 34 key-value pairs and 290 tensors from D:\Users\.ollama\models\blobs\sha256-f2e6b35c8a5ee1ff512f5d6fa6c9b521ce03f534960d30d2fa13b3f737a5691c (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 0.5B Instruct Abliterated llama_model_loader: - kv 3: general.finetune str = Instruct-abliterated llama_model_loader: - kv 4: general.basename str = Qwen2.5 llama_model_loader: - kv 5: general.size_label str = 0.5B llama_model_loader: - kv 6: general.license str = apache-2.0 llama_model_loader: - kv 7: general.license.link str = https://huggingface.co/huihui-ai/Qwen... llama_model_loader: - kv 8: general.base_model.count u32 = 1 llama_model_loader: - kv 9: general.base_model.0.name str = Qwen2.5 0.5B Instruct 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/Qwen2.5-0... llama_model_loader: - kv 12: general.tags arr[str,4] = ["chat", "abliterated", "uncensored",... llama_model_loader: - kv 13: general.languages arr[str,1] = ["en"] llama_model_loader: - kv 14: qwen2.block_count u32 = 24 llama_model_loader: - kv 15: qwen2.context_length u32 = 32768 llama_model_loader: - kv 16: qwen2.embedding_length u32 = 896 llama_model_loader: - kv 17: qwen2.feed_forward_length u32 = 4864 llama_model_loader: - kv 18: qwen2.attention.head_count u32 = 14 llama_model_loader: - kv 19: qwen2.attention.head_count_kv u32 = 2 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,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 26: tokenizer.ggml.token_type arr[i32,151936] = [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: 121 tensors llama_model_loader: - type q5_0: 132 tensors llama_model_loader: - type q8_0: 13 tensors llama_model_loader: - type q4_K: 12 tensors llama_model_loader: - type q6_K: 12 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 373.71 MiB (6.35 BPW) time=2025-03-26T08:16:48.671+08:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" load: special tokens cache size = 22 load: token to piece cache size = 0.9310 MB print_info: arch = qwen2 print_info: vocab_only = 0 print_info: n_ctx_train = 32768 print_info: n_embd = 896 print_info: n_layer = 24 print_info: n_head = 14 print_info: n_head_kv = 2 print_info: n_rot = 64 print_info: n_swa = 0 print_info: n_embd_head_k = 64 print_info: n_embd_head_v = 64 print_info: n_gqa = 7 print_info: n_embd_k_gqa = 128 print_info: n_embd_v_gqa = 128 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-06 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: n_ff = 4864 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 2 print_info: rope scaling = linear print_info: freq_base_train = 1000000.0 print_info: freq_scale_train = 1 print_info: n_ctx_orig_yarn = 32768 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 1B print_info: model params = 494.03 M print_info: general.name = Qwen2.5 0.5B Instruct Abliterated print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' print_info: LF token = 198 'Ċ' print_info: FIM PRE token = 151659 '<|fim_prefix|>' print_info: FIM SUF token = 151661 '<|fim_suffix|>' print_info: FIM MID token = 151660 '<|fim_middle|>' print_info: FIM PAD token = 151662 '<|fim_pad|>' print_info: FIM REP token = 151663 '<|repo_name|>' print_info: FIM SEP token = 151664 '<|file_sep|>' print_info: EOG token = 151643 '<|endoftext|>' print_info: EOG token = 151645 '<|im_end|>' print_info: EOG token = 151662 '<|fim_pad|>' print_info: EOG token = 151663 '<|repo_name|>' print_info: EOG token = 151664 '<|file_sep|>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: CPU model buffer size = 373.71 MiB llama_init_from_model: n_seq_max = 4 llama_init_from_model: n_ctx = 8192 llama_init_from_model: n_ctx_per_seq = 2048 llama_init_from_model: n_batch = 2048 llama_init_from_model: n_ubatch = 512 llama_init_from_model: flash_attn = 0 llama_init_from_model: freq_base = 1000000.0 llama_init_from_model: freq_scale = 1 llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (32768) -- the full capacity of the model will not be utilized llama_kv_cache_init: kv_size = 8192, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 24, can_shift = 1 llama_kv_cache_init: CPU KV buffer size = 96.00 MiB llama_init_from_model: KV self size = 96.00 MiB, K (f16): 48.00 MiB, V (f16): 48.00 MiB llama_init_from_model: CPU output buffer size = 2.33 MiB llama_init_from_model: CPU compute buffer size = 300.25 MiB llama_init_from_model: graph nodes = 846 llama_init_from_model: graph splits = 1 time=2025-03-26T08:16:49.172+08:00 level=INFO source=server.go:619 msg="llama runner started in 0.75 seconds" ..\ggml\src\ggml.c:1721: GGML_ASSERT(tensor->op == GGML_OP_UNARY) failed [GIN] 2025/03/26 - 08:16:49 | 200 | 1.287076s | 127.0.0.1 | POST "/api/chat" time=2025-03-26T08:16:49.322+08:00 level=ERROR source=server.go:449 msg="llama runner terminated" error="exit status 0xc0000409" ### Relevant log output ```shell ``` ### OS Windows ### GPU _No response_ ### CPU Intel ### Ollama version 0.6.3-rc0
GiteaMirror added the bug label 2026-04-29 01:47:02 -05:00
GiteaMirror commented 2026-04-29 01:47:08 -05:00
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@rick-github commented on GitHub (Mar 26, 2025):

#9509

<!-- gh-comment-id:2753450245 --> @rick-github commented on GitHub (Mar 26, 2025): #9509
GiteaMirror commented 2026-04-29 01:47:13 -05:00
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@bmb-li commented on GitHub (Mar 26, 2025):

回退到0.5.12 正常，其后更新的版本都是这个问题。电脑比较旧，仅CPU运行。

<!-- gh-comment-id:2753784000 --> @bmb-li commented on GitHub (Mar 26, 2025): 回退到0.5.12 正常，其后更新的版本都是这个问题。电脑比较旧，仅CPU运行。
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