在从0.20升级到0.27后,ollama以非常低的速度运行gemma 2 9b。我认为操作系统没有耗尽显存,因为gemma 2仅占用6.8G(q_4_0)显存,而我的笔记本电脑有8G显存。然而,其他9b型号的q4_0运行起来就像glm4一样顺畅。这是ollama的bug还是gemma 2本身的问题?
Windows
Nvidia
Intel
0.27
ccrfmcuu1#
服务器日志有助于诊断问题。
iyfjxgzm2#
服务器日志对于诊断问题是有帮助的。
2024/07/21 07:09:47 routes.go:1096: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:D:\\AGI\\ollama_models 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://*] OLLAMA_RUNNERS_DIR:C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" time=2024-07-21T07:09:47.466+08:00 level=INFO source=images.go:778 msg="total blobs: 77" time=2024-07-21T07:09:47.559+08:00 level=INFO source=images.go:785 msg="total unused blobs removed: 0" time=2024-07-21T07:09:47.562+08:00 level=INFO source=routes.go:1143 msg="Listening on 127.0.0.1:11434 (version 0.2.7)" time=2024-07-21T07:09:47.566+08:00 level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cuda_v11.3 rocm_v6.1 cpu cpu_avx cpu_avx2]" time=2024-07-21T07:09:47.567+08:00 level=INFO source=gpu.go:205 msg="looking for compatible GPUs" time=2024-07-21T07:09:48.289+08:00 level=INFO source=gpu.go:287 msg="detected OS VRAM overhead" id=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda compute=8.6 driver=12.1 name="NVIDIA GeForce RTX 3070 Ti Laptop GPU" overhead="918.0 MiB" time=2024-07-21T07:09:48.294+08:00 level=INFO source=types.go:105 msg="inference compute" id=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda compute=8.6 driver=12.1 name="NVIDIA GeForce RTX 3070 Ti Laptop GPU" total="8.0 GiB" available="6.9 GiB" [GIN] 2024/07/21 - 07:10:23 | 200 | 1.1431ms | 127.0.0.1 | HEAD "/" time=2024-07-21T07:10:23.868+08:00 level=WARN source=routes.go:817 msg="bad manifest filepath" name=hub/bacx/studybuddy:latest error="open D:\\AGI\\ollama_models\\blobs\\sha256-c65468c33ec86e462ef2a5eff135cbe40b4e7179b72806048034ccc9dd671eb6: The system cannot find the file specified." [GIN] 2024/07/21 - 07:10:23 | 200 | 59.0374ms | 127.0.0.1 | GET "/api/tags" [GIN] 2024/07/21 - 07:10:39 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:10:39 | 200 | 41.6721ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:10:39.312+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=40 layers.split="" memory.available="[6.9 GiB]" memory.required.full="7.8 GiB" memory.required.partial="6.8 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.8 GiB]" memory.weights.total="5.3 GiB" memory.weights.repeating="4.6 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T07:10:39.325+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-befd260af00133c21746d65696658a69103b53287fee1a6d544e8f972de05d67 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 40 --no-mmap --parallel 1 --port 49780" time=2024-07-21T07:10:39.357+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T07:10:39.359+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T07:10:39.360+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="13488" timestamp=1721517040 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="13488" timestamp=1721517040 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="49780" tid="13488" timestamp=1721517040 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-befd260af00133c21746d65696658a69103b53287fee1a6d544e8f972de05d67 (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 = gemma2 llama_model_loader: - kv 1: general.name str = merged llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 15 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_K: 252 tensors llama_model_loader: - type q6_K: 43 tensors llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.36 GiB (4.98 BPW) llm_load_print_meta: general.name = merged llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 time=2024-07-21T07:10:40.379+08:00 level=INFO source=server.go:612 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 40 repeating layers to GPU llm_load_tensors: offloaded 40/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1677.17 MiB llm_load_tensors: CUDA0 buffer size = 4529.00 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA_Host KV buffer size = 32.00 MiB llama_kv_cache_init: CUDA0 KV buffer size = 640.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 16.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 30 INFO [wmain] model loaded | tid="13488" timestamp=1721517046 time=2024-07-21T07:10:46.468+08:00 level=INFO source=server.go:617 msg="llama runner started in 7.11 seconds" [GIN] 2024/07/21 - 07:10:46 | 200 | 7.2349256s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:17:43 | 200 | 5m40s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:18:01 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:18:01 | 200 | 85.0611ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:18:02.142+08:00 level=INFO source=sched.go:495 msg="updated VRAM based on existing loaded models" gpu=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda total="8.0 GiB" available="48.8 MiB" time=2024-07-21T07:18:03.339+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=42 layers.split="" memory.available="[6.8 GiB]" memory.required.full="6.8 GiB" memory.required.partial="6.1 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.1 GiB]" memory.weights.total="4.4 GiB" memory.weights.repeating="3.7 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T07:18:03.350+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-ba678f3760a834f86247d0fd1ad0ff6d62ba9b030774d0c1bf1c38835979b2d4 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 42 --no-mmap --parallel 1 --port 50143" time=2024-07-21T07:18:03.389+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T07:18:03.389+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T07:18:03.400+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="11612" timestamp=1721517484 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="11612" timestamp=1721517484 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="50143" tid="11612" timestamp=1721517484 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-ba678f3760a834f86247d0fd1ad0ff6d62ba9b030774d0c1bf1c38835979b2d4 (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 = gemma2 llama_model_loader: - kv 1: general.name str = merged llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 12 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... time=2024-07-21T07:18:04.948+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model" llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q3_K: 168 tensors llama_model_loader: - type q4_K: 122 tensors llama_model_loader: - type q5_K: 4 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q3_K - Medium llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 4.43 GiB (4.12 BPW) llm_load_print_meta: general.name = merged llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 42 repeating layers to GPU llm_load_tensors: offloaded 42/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1435.56 MiB llm_load_tensors: CUDA0 buffer size = 3817.62 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA0 KV buffer size = 672.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 15.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 4 INFO [wmain] model loaded | tid="11612" timestamp=1721517491 time=2024-07-21T07:18:11.866+08:00 level=INFO source=server.go:617 msg="llama runner started in 8.48 seconds" [GIN] 2024/07/21 - 07:18:11 | 200 | 9.90228s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:22:14 | 200 | 3m58s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:22:25 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:22:25 | 200 | 136.1339ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:22:25.318+08:00 level=INFO source=sched.go:495 msg="updated VRAM based on existing loaded models" gpu=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda total="8.0 GiB" available="640.9 MiB" time=2024-07-21T07:22:26.450+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=41 layers.split="" memory.available="[6.7 GiB]" memory.required.full="7.5 GiB" memory.required.partial="6.7 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.7 GiB]" memory.weights.total="5.0 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T07:22:26.462+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 41 --no-mmap --parallel 1 --port 50231" time=2024-07-21T07:22:26.526+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T07:22:26.526+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T07:22:26.529+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="9252" timestamp=1721517748 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="9252" timestamp=1721517748 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="50231" tid="9252" timestamp=1721517748 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 (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 = gemma2 llama_model_loader: - kv 1: general.name str = gemma-2-9b-it llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 2 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... time=2024-07-21T07:22:28.117+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model" llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_0: 294 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_0 llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.06 GiB (4.71 BPW) llm_load_print_meta: general.name = gemma-2-9b-it llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 41 repeating layers to GPU llm_load_tensors: offloaded 41/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1541.93 MiB llm_load_tensors: CUDA0 buffer size = 4361.05 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA_Host KV buffer size = 16.00 MiB llama_kv_cache_init: CUDA0 KV buffer size = 656.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 16.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 17 INFO [wmain] model loaded | tid="9252" timestamp=1721517757 time=2024-07-21T07:22:38.050+08:00 level=INFO source=server.go:617 msg="llama runner started in 11.52 seconds" [GIN] 2024/07/21 - 07:22:38 | 200 | 12.9035189s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:25:36 | 200 | 59.9902702s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:25:48 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:25:48 | 200 | 62.6399ms | 127.0.0.1 | POST "/api/show" [GIN] 2024/07/21 - 07:26:40 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:26:41 | 200 | 1.3670033s | 127.0.0.1 | DELETE "/api/delete" [GIN] 2024/07/21 - 07:26:48 | 200 | 0s | 127.0.0.1 | HEAD "/" time=2024-07-21T07:26:48.291+08:00 level=WARN source=routes.go:817 msg="bad manifest filepath" name=hub/bacx/studybuddy:latest error="open D:\\AGI\\ollama_models\\blobs\\sha256-c65468c33ec86e462ef2a5eff135cbe40b4e7179b72806048034ccc9dd671eb6: The system cannot find the file specified." [GIN] 2024/07/21 - 07:26:48 | 200 | 171.5556ms | 127.0.0.1 | GET "/api/tags" [GIN] 2024/07/21 - 07:26:59 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:26:59 | 404 | 0s | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:27:32.046+08:00 level=INFO source=images.go:1047 msg="request failed: Head \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232702Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=058dc757384f0a42d66693feb1e1e2f95cbe7e4925e98b1e2d4e0331b631abf3\": dial tcp 104.18.8.90:443: i/o timeout" [GIN] 2024/07/21 - 07:27:32 | 200 | 32.7627094s | 127.0.0.1 | POST "/api/pull" [GIN] 2024/07/21 - 07:27:48 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:27:48 | 404 | 0s | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:28:06.136+08:00 level=INFO source=download.go:136 msg="downloading ff1d1fc78170 in 55 100 MB part(s)" time=2024-07-21T07:28:37.059+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.059+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.061+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 2 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.062+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 31 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.075+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.075+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.075+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.075+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 54 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.075+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 38 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.075+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 4 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.091+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.091+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 22 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.106+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.106+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 45 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.122+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.122+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.122+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 1 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.122+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 35 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.122+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.122+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 50 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.122+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.122+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.122+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 24 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.122+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 13 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.138+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.138+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 10 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:28:37.196+08:00 level=INFO source=images.go:1047 msg="request failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout" time=2024-07-21T07:28:37.196+08:00 level=INFO source=download.go:178 msg="ff1d1fc78170 part 25 attempt 0 failed: Get \"https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/ff/ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20240720%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20240720T232807Z&X-Amz-Expires=1200&X-Amz-SignedHeaders=host&X-Amz-Signature=428592c40b79461663b67f7dfef07ad8b400cc6024fa095eb10494afd744febb\": dial tcp 104.18.8.90:443: i/o timeout, retrying in 1s" time=2024-07-21T07:31:34.243+08:00 level=INFO source=images.go:1047 msg="request failed: Head \"https://registry.ollama.ai/v2/library/gemma2/blobs/sha256:109037bec39c0becc8221222ae23557559bc594290945a2c4221ab4f303b8871\": dial tcp 172.67.182.229:443: i/o timeout" [GIN] 2024/07/21 - 07:31:34 | 200 | 3m45s | 127.0.0.1 | POST "/api/pull" [GIN] 2024/07/21 - 07:31:54 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 07:31:54 | 404 | 503.3µs | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:32:11.792+08:00 level=INFO source=download.go:136 msg="downloading 109037bec39c in 1 136 B part(s)" time=2024-07-21T07:32:15.018+08:00 level=INFO source=download.go:136 msg="downloading 097a36493f71 in 1 8.4 KB part(s)" time=2024-07-21T07:32:18.187+08:00 level=INFO source=download.go:136 msg="downloading 10aa81da732e in 1 487 B part(s)" [GIN] 2024/07/21 - 07:32:20 | 200 | 26.1686553s | 127.0.0.1 | POST "/api/pull" [GIN] 2024/07/21 - 07:32:20 | 200 | 80.6173ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T07:32:20.522+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=41 layers.split="" memory.available="[6.7 GiB]" memory.required.full="7.5 GiB" memory.required.partial="6.7 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.7 GiB]" memory.weights.total="5.0 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T07:32:20.534+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 41 --no-mmap --parallel 1 --port 53069" time=2024-07-21T07:32:20.538+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T07:32:20.538+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T07:32:20.540+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="3440" timestamp=1721518340 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="3440" timestamp=1721518340 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="53069" tid="3440" timestamp=1721518340 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 (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 = gemma2 llama_model_loader: - kv 1: general.name str = gemma-2-9b-it llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 2 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_0: 294 tensors llama_model_loader: - type q6_K: 1 tensors time=2024-07-21T07:32:20.793+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model" llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_0 llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.06 GiB (4.71 BPW) llm_load_print_meta: general.name = gemma-2-9b-it llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 41 repeating layers to GPU llm_load_tensors: offloaded 41/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1541.93 MiB llm_load_tensors: CUDA0 buffer size = 4361.05 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA_Host KV buffer size = 16.00 MiB llama_kv_cache_init: CUDA0 KV buffer size = 656.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 16.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 17 INFO [wmain] model loaded | tid="3440" timestamp=1721518348 time=2024-07-21T07:32:28.977+08:00 level=INFO source=server.go:617 msg="llama runner started in 8.44 seconds" [GIN] 2024/07/21 - 07:32:28 | 200 | 8.6336192s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:35:37 | 200 | 53.5176442s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 07:35:51 | 200 | 0s | 127.0.0.1 | HEAD "/" time=2024-07-21T07:35:51.696+08:00 level=WARN source=routes.go:817 msg="bad manifest filepath" name=hub/bacx/studybuddy:latest error="open D:\\AGI\\ollama_models\\blobs\\sha256-c65468c33ec86e462ef2a5eff135cbe40b4e7179b72806048034ccc9dd671eb6: The system cannot find the file specified." [GIN] 2024/07/21 - 07:35:51 | 200 | 21.012ms | 127.0.0.1 | GET "/api/tags"
v1l68za43#
并非所有层都在0.2.7版本的GPU上加载:
llm_load_tensors: offloading 41 repeating layers to GPU llm_load_tensors: offloaded 41/43 layers to GPU
你有0.2.0版本的相应日志吗?
swvgeqrz4#
你的卡片上并非所有的8G都可用于ollama: memory.available="[6.8 GiB]"。nvidia-smi的输出是什么?
memory.available="[6.8 GiB]"
nvidia-smi
jslywgbw5#
2024/07/21 09:23:25 routes.go:1033: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:D:\\AGI\\ollama_models 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://*] OLLAMA_RUNNERS_DIR:C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" time=2024-07-21T09:23:25.512+08:00 level=INFO source=images.go:751 msg="total blobs: 77" time=2024-07-21T09:23:25.515+08:00 level=INFO source=images.go:758 msg="total unused blobs removed: 0" time=2024-07-21T09:23:25.518+08:00 level=INFO source=routes.go:1080 msg="Listening on 127.0.0.1:11434 (version 0.2.0)" time=2024-07-21T09:23:25.518+08:00 level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu cpu_avx cpu_avx2 cuda_v11.3 rocm_v5.7]" time=2024-07-21T09:23:25.518+08:00 level=INFO source=gpu.go:205 msg="looking for compatible GPUs" time=2024-07-21T09:23:26.766+08:00 level=INFO source=types.go:103 msg="inference compute" id=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda compute=8.6 driver=12.1 name="NVIDIA GeForce RTX 3070 Ti Laptop GPU" total="8.0 GiB" available="6.9 GiB" [GIN] 2024/07/21 - 09:23:39 | 200 | 562.4µs | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 09:23:39 | 200 | 52.121ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T09:23:40.138+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=42 layers.split="" memory.available="[7.5 GiB]" memory.required.full="7.5 GiB" memory.required.partial="6.8 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.8 GiB]" memory.weights.total="5.0 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T09:23:40.157+08:00 level=INFO source=server.go:375 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 42 --no-mmap --parallel 1 --port 57976" time=2024-07-21T09:23:40.225+08:00 level=INFO source=sched.go:477 msg="loaded runners" count=1 time=2024-07-21T09:23:40.225+08:00 level=INFO source=server.go:563 msg="waiting for llama runner to start responding" time=2024-07-21T09:23:40.225+08:00 level=INFO source=server.go:604 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="2304" timestamp=1721525021 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="2304" timestamp=1721525021 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="57976" tid="2304" timestamp=1721525021 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 (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 = gemma2 llama_model_loader: - kv 1: general.name str = gemma-2-9b-it llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 2 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... time=2024-07-21T09:23:41.755+08:00 level=INFO source=server.go:604 msg="waiting for server to become available" status="llm server loading model" llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_0: 294 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_0 llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.06 GiB (4.71 BPW) llm_load_print_meta: general.name = gemma-2-9b-it llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 42 repeating layers to GPU llm_load_tensors: offloaded 42/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1435.56 MiB llm_load_tensors: CUDA0 buffer size = 4467.42 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA0 KV buffer size = 672.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 15.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 4 INFO [wmain] model loaded | tid="2304" timestamp=1721525031 time=2024-07-21T09:23:51.769+08:00 level=INFO source=server.go:609 msg="llama runner started in 11.54 seconds" [GIN] 2024/07/21 - 09:23:51 | 200 | 11.7944928s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 09:25:32 | 200 | 28.1855238s | 127.0.0.1 | POST "/api/chat"
luaexgnf6#
并非您卡片上的所有8G都可用于ollama:memory.available="[6.8 GiB]"。nvidia-smi的输出是什么?0.20确实运行得非常顺畅
yv5phkfx7#
在我卸载并重新安装0.27版本后,它也能顺利运行gemma2。我认为与其直接升级,还不如先卸载再重新安装ollama。这是日志:
2024/07/21 09:32:08 routes.go:1096: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:D:\\AGI\\ollama_models 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://*] OLLAMA_RUNNERS_DIR:C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" time=2024-07-21T09:32:08.218+08:00 level=INFO source=images.go:778 msg="total blobs: 77" time=2024-07-21T09:32:08.221+08:00 level=INFO source=images.go:785 msg="total unused blobs removed: 0" time=2024-07-21T09:32:08.224+08:00 level=INFO source=routes.go:1143 msg="Listening on 127.0.0.1:11434 (version 0.2.7)" time=2024-07-21T09:32:08.225+08:00 level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu_avx2 cuda_v11.3 rocm_v6.1 cpu cpu_avx]" time=2024-07-21T09:32:08.225+08:00 level=INFO source=gpu.go:205 msg="looking for compatible GPUs" time=2024-07-21T09:32:08.556+08:00 level=INFO source=gpu.go:287 msg="detected OS VRAM overhead" id=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda compute=8.6 driver=12.1 name="NVIDIA GeForce RTX 3070 Ti Laptop GPU" overhead="641.5 MiB" time=2024-07-21T09:32:08.557+08:00 level=INFO source=types.go:105 msg="inference compute" id=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda compute=8.6 driver=12.1 name="NVIDIA GeForce RTX 3070 Ti Laptop GPU" total="8.0 GiB" available="6.9 GiB" [GIN] 2024/07/21 - 09:32:15 | 200 | 0s | 127.0.0.1 | GET "/api/version" [GIN] 2024/07/21 - 09:32:23 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 09:32:23 | 200 | 19.0269ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T09:32:24.040+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=42 layers.split="" memory.available="[6.9 GiB]" memory.required.full="7.5 GiB" memory.required.partial="6.8 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[6.8 GiB]" memory.weights.total="5.0 GiB" memory.weights.repeating="4.3 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T09:32:24.045+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 42 --no-mmap --parallel 1 --port 59469" time=2024-07-21T09:32:24.108+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T09:32:24.110+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T09:32:24.111+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="3592" timestamp=1721525545 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="3592" timestamp=1721525545 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="59469" tid="3592" timestamp=1721525545 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-ff1d1fc78170d787ee1201778e2dd65ea211654ca5fb7d69b5a2e7b123a50373 (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 = gemma2 llama_model_loader: - kv 1: general.name str = gemma-2-9b-it llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 2 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... time=2024-07-21T09:32:25.884+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model" llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_0: 294 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_0 llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.06 GiB (4.71 BPW) llm_load_print_meta: general.name = gemma-2-9b-it llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 42 repeating layers to GPU llm_load_tensors: offloaded 42/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1435.56 MiB llm_load_tensors: CUDA0 buffer size = 4467.42 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA0 KV buffer size = 672.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 15.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 4 INFO [wmain] model loaded | tid="3592" timestamp=1721525550 time=2024-07-21T09:32:30.170+08:00 level=INFO source=server.go:617 msg="llama runner started in 6.06 seconds" [GIN] 2024/07/21 - 09:32:30 | 200 | 6.1944242s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 09:35:09 | 200 | 21.2028767s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 09:35:19 | 200 | 0s | 127.0.0.1 | HEAD "/" time=2024-07-21T09:35:19.577+08:00 level=WARN source=routes.go:817 msg="bad manifest filepath" name=hub/bacx/studybuddy:latest error="open D:\\AGI\\ollama_models\\blobs\\sha256-c65468c33ec86e462ef2a5eff135cbe40b4e7179b72806048034ccc9dd671eb6: The system cannot find the file specified." [GIN] 2024/07/21 - 09:35:19 | 200 | 4.9597ms | 127.0.0.1 | GET "/api/tags" [GIN] 2024/07/21 - 09:35:30 | 200 | 0s | 127.0.0.1 | HEAD "/" [GIN] 2024/07/21 - 09:35:30 | 200 | 36.1565ms | 127.0.0.1 | POST "/api/show" time=2024-07-21T09:35:30.566+08:00 level=INFO source=sched.go:495 msg="updated VRAM based on existing loaded models" gpu=GPU-59be21cf-1a6f-4733-e579-d85deb64d686 library=cuda total="8.0 GiB" available="241.7 MiB" time=2024-07-21T09:35:31.526+08:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=43 layers.offload=41 layers.split="" memory.available="[7.0 GiB]" memory.required.full="7.8 GiB" memory.required.partial="7.0 GiB" memory.required.kv="672.0 MiB" memory.required.allocations="[7.0 GiB]" memory.weights.total="5.3 GiB" memory.weights.repeating="4.6 GiB" memory.weights.nonrepeating="717.8 MiB" memory.graph.full="507.0 MiB" memory.graph.partial="1.2 GiB" time=2024-07-21T09:35:31.529+08:00 level=INFO source=server.go:383 msg="starting llama server" cmd="C:\\Users\\Raven\\AppData\\Local\\Programs\\Ollama\\ollama_runners\\cuda_v11.3\\ollama_llama_server.exe --model D:\\AGI\\ollama_models\\blobs\\sha256-befd260af00133c21746d65696658a69103b53287fee1a6d544e8f972de05d67 --ctx-size 2048 --batch-size 512 --embedding --log-disable --n-gpu-layers 41 --no-mmap --parallel 1 --port 60108" time=2024-07-21T09:35:31.534+08:00 level=INFO source=sched.go:437 msg="loaded runners" count=1 time=2024-07-21T09:35:31.534+08:00 level=INFO source=server.go:571 msg="waiting for llama runner to start responding" time=2024-07-21T09:35:31.534+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server error" INFO [wmain] build info | build=3337 commit="a8db2a9c" tid="16724" timestamp=1721525731 INFO [wmain] system info | n_threads=10 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 0 | " tid="16724" timestamp=1721525731 total_threads=20 INFO [wmain] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="60108" tid="16724" timestamp=1721525731 llama_model_loader: loaded meta data with 29 key-value pairs and 464 tensors from D:\AGI\ollama_models\blobs\sha256-befd260af00133c21746d65696658a69103b53287fee1a6d544e8f972de05d67 (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 = gemma2 llama_model_loader: - kv 1: general.name str = merged llama_model_loader: - kv 2: gemma2.context_length u32 = 8192 llama_model_loader: - kv 3: gemma2.embedding_length u32 = 3584 llama_model_loader: - kv 4: gemma2.block_count u32 = 42 llama_model_loader: - kv 5: gemma2.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: gemma2.attention.head_count u32 = 16 llama_model_loader: - kv 7: gemma2.attention.head_count_kv u32 = 8 llama_model_loader: - kv 8: gemma2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 9: gemma2.attention.key_length u32 = 256 llama_model_loader: - kv 10: gemma2.attention.value_length u32 = 256 llama_model_loader: - kv 11: general.file_type u32 = 15 llama_model_loader: - kv 12: gemma2.attn_logit_softcapping f32 = 50.000000 llama_model_loader: - kv 13: gemma2.final_logit_softcapping f32 = 30.000000 llama_model_loader: - kv 14: gemma2.attention.sliding_window u32 = 4096 llama_model_loader: - kv 15: tokenizer.ggml.model str = llama llama_model_loader: - kv 16: tokenizer.ggml.pre str = default llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,256000] = ["<pad>", "<eos>", "<bos>", "<unk>", ... llama_model_loader: - kv 18: tokenizer.ggml.scores arr[f32,256000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 19: tokenizer.ggml.token_type arr[i32,256000] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 20: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 21: tokenizer.ggml.eos_token_id u32 = 1 llama_model_loader: - kv 22: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 25: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 26: tokenizer.chat_template str = {{ bos_token }}{% if messages[0]['rol... llama_model_loader: - kv 27: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 28: general.quantization_version u32 = 2 llama_model_loader: - type f32: 169 tensors llama_model_loader: - type q4_K: 252 tensors llama_model_loader: - type q6_K: 43 tensors time=2024-07-21T09:35:31.787+08:00 level=INFO source=server.go:612 msg="waiting for server to become available" status="llm server loading model" llm_load_vocab: special tokens cache size = 364 llm_load_vocab: token to piece cache size = 1.6014 MB llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = gemma2 llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 256000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: vocab_only = 0 llm_load_print_meta: n_ctx_train = 8192 llm_load_print_meta: n_embd = 3584 llm_load_print_meta: n_layer = 42 llm_load_print_meta: n_head = 16 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_rot = 256 llm_load_print_meta: n_swa = 4096 llm_load_print_meta: n_embd_head_k = 256 llm_load_print_meta: n_embd_head_v = 256 llm_load_print_meta: n_gqa = 2 llm_load_print_meta: n_embd_k_gqa = 2048 llm_load_print_meta: n_embd_v_gqa = 2048 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 = 14336 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 = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_ctx_orig_yarn = 8192 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: model type = 9B llm_load_print_meta: model ftype = Q4_K - Medium llm_load_print_meta: model params = 9.24 B llm_load_print_meta: model size = 5.36 GiB (4.98 BPW) llm_load_print_meta: general.name = merged llm_load_print_meta: BOS token = 2 '<bos>' llm_load_print_meta: EOS token = 1 '<eos>' llm_load_print_meta: UNK token = 3 '<unk>' llm_load_print_meta: PAD token = 0 '<pad>' llm_load_print_meta: LF token = 227 '<0x0A>' llm_load_print_meta: EOT token = 107 '<end_of_turn>' llm_load_print_meta: max token length = 93 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 3070 Ti Laptop GPU, compute capability 8.6, VMM: yes llm_load_tensors: ggml ctx size = 0.41 MiB llm_load_tensors: offloading 41 repeating layers to GPU llm_load_tensors: offloaded 41/43 layers to GPU llm_load_tensors: CUDA_Host buffer size = 1556.37 MiB llm_load_tensors: CUDA0 buffer size = 4649.80 MiB llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 llama_new_context_with_model: flash_attn = 0 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_kv_cache_init: CUDA_Host KV buffer size = 16.00 MiB llama_kv_cache_init: CUDA0 KV buffer size = 656.00 MiB llama_new_context_with_model: KV self size = 672.00 MiB, K (f16): 336.00 MiB, V (f16): 336.00 MiB llama_new_context_with_model: CUDA_Host output buffer size = 0.99 MiB llama_new_context_with_model: CUDA0 compute buffer size = 1224.77 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 16.01 MiB llama_new_context_with_model: graph nodes = 1690 llama_new_context_with_model: graph splits = 17 INFO [wmain] model loaded | tid="16724" timestamp=1721525737 time=2024-07-21T09:35:37.353+08:00 level=INFO source=server.go:617 msg="llama runner started in 5.82 seconds" [GIN] 2024/07/21 - 09:35:37 | 200 | 6.8512463s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 09:37:04 | 200 | 32.4115701s | 127.0.0.1 | POST "/api/chat" [GIN] 2024/07/21 - 09:38:30 | 200 | 35.5102982s | 127.0.0.1 | POST "/api/chat"
7条答案
按热度按时间ccrfmcuu1#
服务器日志有助于诊断问题。
iyfjxgzm2#
服务器日志对于诊断问题是有帮助的。
v1l68za43#
并非所有层都在0.2.7版本的GPU上加载:
你有0.2.0版本的相应日志吗?
swvgeqrz4#
你的卡片上并非所有的8G都可用于ollama:
memory.available="[6.8 GiB]"
。nvidia-smi
的输出是什么?jslywgbw5#
并非所有层都在0.2.7版本的GPU上加载:
你有0.2.0版本的相应日志吗?
luaexgnf6#
并非您卡片上的所有8G都可用于ollama:
memory.available="[6.8 GiB]"
。nvidia-smi
的输出是什么?0.20确实运行得非常顺畅
yv5phkfx7#
在我卸载并重新安装0.27版本后,它也能顺利运行gemma2。我认为与其直接升级,还不如先卸载再重新安装ollama。
这是日志: