llama.cpp
llama.cpp copied to clipboard
Published
2 months ago
•
ggml-org
ggml-org
Bug: When --parallel 4 is turned ON, the inferring result is apparently like fool .But when --parallel 4 is turned OFF everything is OK ?
What happened?
#####CMD which Works Normally: CUDA_VISIBLE_DEVICES=0 ./llama-server -m /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf --gpu-layers 33 -cb --ctx-size 16128 --flash-attn --batch-size 512 --chat-template llama3 --port 8866 --host 0.0.0.0
#####CMD which Works NOT Normally:
CUDA_VISIBLE_DEVICES=0 ./llama-server -m /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf --gpu-layers 33 -cb --parallel 4 --ctx-size 16128 --flash-attn --batch-size 512 --chat-template llama3 --port 8866 --host 0.0.0.0
ubuntu@VM-0-16-ubuntu:~$ nvidia-smi
Thu Aug 8 21:22:25 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.183.01 Driver Version: 535.183.01 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 Tesla V100-SXM2-32GB Off | 00000000:00:08.0 Off | 0 |
| N/A 34C P0 39W / 300W | 10194MiB / 32768MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=======================================================================================| | 0 N/A N/A 35134 C ./llama-server 10192MiB | +---------------------------------------------------------------------------------------+
Name and Version
ubuntu@VM-0-16-ubuntu:~/llama.cpp$ ^C ubuntu@VM-0-16-ubuntu:~/llama.cpp$ ./llama-cli --version version: 3549 (afd27f01) built with cc (Ubuntu 9.5.0-1ubuntu1~22.04) 9.5.0 for x86_64-linux-gnu
What operating system are you seeing the problem on?
Linux
Relevant log output
#####CMD which Works Normally:
CUDA_VISIBLE_DEVICES=0 ./llama-server -m /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf --gpu-layers 33 -cb --ctx-size 16128 --flash-attn --batch-size 512 --chat-template llama3 --port 8866 --host 0.0.0.0
INFO [ main] build info | tid="140562966491136" timestamp=1723124595 build=3549 commit="afd27f01"
INFO [ main] system info | tid="140562966491136" timestamp=1723124595 n_threads=10 n_threads_batch=-1 total_threads=10 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 0 | AVX512_VNNI = 1 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "
llama_model_loader: loaded meta data with 33 key-value pairs and 291 tensors from /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Models Meta Llama Meta Llama 3.1 8B I...
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = models-meta-llama-Meta-Llama-3.1
llama_model_loader: - kv 5: general.size_label str = 8B
llama_model_loader: - kv 6: general.license str = llama3.1
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 9: llama.block_count u32 = 32
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 4096
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: general.file_type u32 = 7
llama_model_loader: - kv 18: llama.vocab_size u32 = 128256
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 21: tokenizer.ggml.pre str = smaug-bpe
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 27: tokenizer.chat_template str = {% set loop_messages = messages %}{% ...
llama_model_loader: - kv 28: general.quantization_version u32 = 2
llama_model_loader: - kv 29: quantize.imatrix.file str = ./Meta-Llama-3.1-8B-Instruct-GGUF_ima...
llama_model_loader: - kv 30: quantize.imatrix.dataset str = group_40.txt
llama_model_loader: - kv 31: quantize.imatrix.entries_count i32 = 224
llama_model_loader: - kv 32: quantize.imatrix.chunks_count i32 = 68
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q8_0: 226 tensors
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.7999 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 128256
llm_load_print_meta: n_merges = 280147
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 131072
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_layer = 32
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 4
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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 = 0
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 131072
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 = 8B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 8.03 B
llm_load_print_meta: model size = 7.95 GiB (8.50 BPW)
llm_load_print_meta: general.name = Models Meta Llama Meta Llama 3.1 8B Instruct
llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token = 128009 '<|eot_id|>'
llm_load_print_meta: LF token = 128 'Ä'
llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
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: Tesla V100-SXM2-32GB, compute capability 7.0, VMM: yes
llm_load_tensors: ggml ctx size = 0.27 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors: CPU buffer size = 532.31 MiB
llm_load_tensors: CUDA0 buffer size = 7605.33 MiB
.........................................................................................
llama_new_context_with_model: n_ctx = 16128
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 1
llama_new_context_with_model: freq_base = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 2016.00 MiB
llama_new_context_with_model: KV self size = 2016.00 MiB, K (f16): 1008.00 MiB, V (f16): 1008.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 0.98 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 258.50 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 39.51 MiB
llama_new_context_with_model: graph nodes = 903
llama_new_context_with_model: graph splits = 2
INFO [ init] initializing slots | tid="140562966491136" timestamp=1723124598 n_slots=1
INFO [ init] new slot | tid="140562966491136" timestamp=1723124598 id_slot=0 n_ctx_slot=16128
INFO [ main] model loaded | tid="140562966491136" timestamp=1723124598
INFO [ main] chat template | tid="140562966491136" timestamp=1723124598 chat_example="<|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHi there<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHow are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" built_in=false
INFO [ main] HTTP server listening | tid="140562966491136" timestamp=1723124598 n_threads_http="9" port="8866" hostname="0.0.0.0"
INFO [ update_slots] all slots are idle | tid="140562966491136" timestamp=1723124598
INFO [ launch_slot_with_task] slot is processing task | tid="140562966491136" timestamp=1723124772 id_slot=0 id_task=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124772 id_slot=0 id_task=0 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124772 id_slot=0 id_task=0 p0=512
INFO [ print_timings] prompt eval time = 391.14 ms / 907 tokens ( 0.43 ms per token, 2318.87 tokens per second) | tid="140562966491136" timestamp=1723124773 id_slot=0 id_task=0 t_prompt_processing=391.138 n_prompt_tokens_processed=907 t_token=0.4312436604189636 n_tokens_second=2318.874668275647
INFO [ print_timings] generation eval time = 1003.99 ms / 74 runs ( 13.57 ms per token, 73.71 tokens per second) | tid="140562966491136" timestamp=1723124773 id_slot=0 id_task=0 t_token_generation=1003.985 n_decoded=74 t_token=13.567364864864865 n_tokens_second=73.70628047231781
INFO [ print_timings] total time = 1395.12 ms | tid="140562966491136" timestamp=1723124773 id_slot=0 id_task=0 t_prompt_processing=391.138 t_token_generation=1003.985 t_total=1395.123
INFO [ update_slots] slot released | tid="140562966491136" timestamp=1723124773 id_slot=0 id_task=0 n_ctx=16128 n_past=980 n_system_tokens=0 n_cache_tokens=512 truncated=false
INFO [ update_slots] all slots are idle | tid="140562966491136" timestamp=1723124773
INFO [ log_server_request] request | tid="140561439375360" timestamp=1723124773 remote_addr="43.153.18.71" remote_port=57628 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=1024
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=1536
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=2048
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124774 id_slot=0 id_task=76 p0=2560
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124775 id_slot=0 id_task=76 p0=3072
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124775 id_slot=0 id_task=76 p0=3584
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124775 id_slot=0 id_task=76 p0=4096
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124775 id_slot=0 id_task=76 p0=4608
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124776 id_slot=0 id_task=76 p0=5120
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124776 id_slot=0 id_task=76 p0=5632
INFO [ print_timings] prompt eval time = 2921.58 ms / 5756 tokens ( 0.51 ms per token, 1970.17 tokens per second) | tid="140562966491136" timestamp=1723124778 id_slot=0 id_task=76 t_prompt_processing=2921.578 n_prompt_tokens_processed=5756 t_token=0.5075708825573315 n_tokens_second=1970.168176239005
INFO [ print_timings] generation eval time = 2037.78 ms / 133 runs ( 15.32 ms per token, 65.27 tokens per second) | tid="140562966491136" timestamp=1723124778 id_slot=0 id_task=76 t_token_generation=2037.779 n_decoded=133 t_token=15.321646616541353 n_tokens_second=65.26713642647215
INFO [ print_timings] total time = 4959.36 ms | tid="140562966491136" timestamp=1723124778 id_slot=0 id_task=76 t_prompt_processing=2921.578 t_token_generation=2037.779 t_total=4959.357
INFO [ update_slots] slot released | tid="140562966491136" timestamp=1723124778 id_slot=0 id_task=76 n_ctx=16128 n_past=5888 n_system_tokens=0 n_cache_tokens=5632 truncated=false
INFO [ update_slots] all slots are idle | tid="140562966491136" timestamp=1723124778
INFO [ log_server_request] request | tid="140558945218560" timestamp=1723124778 remote_addr="43.153.18.71" remote_port=57638 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ update_slots] all slots are idle | tid="140562966491136" timestamp=1723124778
INFO [ launch_slot_with_task] slot is processing task | tid="140562966491136" timestamp=1723124779 id_slot=0 id_task=222
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124779 id_slot=0 id_task=222 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124779 id_slot=0 id_task=222 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140562966491136" timestamp=1723124779 id_slot=0 id_task=222 p0=1024
^C^CReceived second interrupt, terminating immediately.
####NOT Normally:
ubuntu@VM-0-16-ubuntu:~/llama.cpp$ CUDA_VISIBLE_DEVICES=0 ./llama-server -m /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf --gpu-layers 33 -cb --parallel 4 --ctx-size 16128 --flash-attn --batch-size 512 --chat-template llama3 --port 8866 --host 0.0.0.0
INFO [ main] build info | tid="140411292143616" timestamp=1723125078 build=3549 commit="afd27f01"
INFO [ main] system info | tid="140411292143616" timestamp=1723125078 n_threads=10 n_threads_batch=-1 total_threads=10 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 0 | AVX512_VNNI = 1 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "
llama_model_loader: loaded meta data with 33 key-value pairs and 291 tensors from /home/ubuntu/.cache/huggingface/hub/models--MaziyarPanahi--Meta-Llama-3.1-8B-Instruct-GGUF/snapshots/1f301d86d760b435a11a56de3863bc0121bfb98f/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = llama
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Models Meta Llama Meta Llama 3.1 8B I...
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = models-meta-llama-Meta-Llama-3.1
llama_model_loader: - kv 5: general.size_label str = 8B
llama_model_loader: - kv 6: general.license str = llama3.1
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv 9: llama.block_count u32 = 32
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 4096
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: general.file_type u32 = 7
llama_model_loader: - kv 18: llama.vocab_size u32 = 128256
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128
llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 21: tokenizer.ggml.pre str = smaug-bpe
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 27: tokenizer.chat_template str = {% set loop_messages = messages %}{% ...
llama_model_loader: - kv 28: general.quantization_version u32 = 2
llama_model_loader: - kv 29: quantize.imatrix.file str = ./Meta-Llama-3.1-8B-Instruct-GGUF_ima...
llama_model_loader: - kv 30: quantize.imatrix.dataset str = group_40.txt
llama_model_loader: - kv 31: quantize.imatrix.entries_count i32 = 224
llama_model_loader: - kv 32: quantize.imatrix.chunks_count i32 = 68
llama_model_loader: - type f32: 65 tensors
llama_model_loader: - type q8_0: 226 tensors
llm_load_vocab: special tokens cache size = 256
llm_load_vocab: token to piece cache size = 0.7999 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = BPE
llm_load_print_meta: n_vocab = 128256
llm_load_print_meta: n_merges = 280147
llm_load_print_meta: vocab_only = 0
llm_load_print_meta: n_ctx_train = 131072
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_layer = 32
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 128
llm_load_print_meta: n_embd_head_v = 128
llm_load_print_meta: n_gqa = 4
llm_load_print_meta: n_embd_k_gqa = 1024
llm_load_print_meta: n_embd_v_gqa = 1024
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
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 = 0
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 500000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 131072
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 = 8B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 8.03 B
llm_load_print_meta: model size = 7.95 GiB (8.50 BPW)
llm_load_print_meta: general.name = Models Meta Llama Meta Llama 3.1 8B Instruct
llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
llm_load_print_meta: EOS token = 128009 '<|eot_id|>'
llm_load_print_meta: LF token = 128 'Ä'
llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
llm_load_print_meta: max token length = 256
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: Tesla V100-SXM2-32GB, compute capability 7.0, VMM: yes
llm_load_tensors: ggml ctx size = 0.27 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
llm_load_tensors: CPU buffer size = 532.31 MiB
llm_load_tensors: CUDA0 buffer size = 7605.33 MiB
.........................................................................................
llama_new_context_with_model: n_ctx = 16128
llama_new_context_with_model: n_batch = 512
llama_new_context_with_model: n_ubatch = 512
llama_new_context_with_model: flash_attn = 1
llama_new_context_with_model: freq_base = 500000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 2016.00 MiB
llama_new_context_with_model: KV self size = 2016.00 MiB, K (f16): 1008.00 MiB, V (f16): 1008.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 2.45 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 258.50 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 39.51 MiB
llama_new_context_with_model: graph nodes = 903
llama_new_context_with_model: graph splits = 2
INFO [ init] initializing slots | tid="140411292143616" timestamp=1723125081 n_slots=4
INFO [ init] new slot | tid="140411292143616" timestamp=1723125081 id_slot=0 n_ctx_slot=4032
INFO [ init] new slot | tid="140411292143616" timestamp=1723125081 id_slot=1 n_ctx_slot=4032
INFO [ init] new slot | tid="140411292143616" timestamp=1723125081 id_slot=2 n_ctx_slot=4032
INFO [ init] new slot | tid="140411292143616" timestamp=1723125081 id_slot=3 n_ctx_slot=4032
INFO [ main] model loaded | tid="140411292143616" timestamp=1723125081
INFO [ main] chat template | tid="140411292143616" timestamp=1723125081 chat_example="<|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHi there<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHow are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" built_in=false
INFO [ main] HTTP server listening | tid="140411292143616" timestamp=1723125081 n_threads_http="9" port="8866" hostname="0.0.0.0"
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125081
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125094 id_slot=0 id_task=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125094 id_slot=0 id_task=0 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125094 id_slot=0 id_task=0 p0=512
INFO [ print_timings] prompt eval time = 391.33 ms / 907 tokens ( 0.43 ms per token, 2317.74 tokens per second) | tid="140411292143616" timestamp=1723125096 id_slot=0 id_task=0 t_prompt_processing=391.329 n_prompt_tokens_processed=907 t_token=0.4314542447629548 n_tokens_second=2317.7428710880104
INFO [ print_timings] generation eval time = 1014.42 ms / 74 runs ( 13.71 ms per token, 72.95 tokens per second) | tid="140411292143616" timestamp=1723125096 id_slot=0 id_task=0 t_token_generation=1014.416 n_decoded=74 t_token=13.708324324324325 n_tokens_second=72.94837620857714
INFO [ print_timings] total time = 1405.75 ms | tid="140411292143616" timestamp=1723125096 id_slot=0 id_task=0 t_prompt_processing=391.329 t_token_generation=1014.416 t_total=1405.7450000000001
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125096 id_slot=0 id_task=0 n_ctx=16128 n_past=980 n_system_tokens=0 n_cache_tokens=512 truncated=false
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125096
INFO [ log_server_request] request | tid="140409762209792" timestamp=1723125096 remote_addr="43.153.18.71" remote_port=36174 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125096 id_slot=1 id_task=76
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125096 id_slot=1 id_task=76 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125096 id_slot=1 id_task=76 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125096 id_slot=1 id_task=76 p0=1024
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125096 id_slot=1 id_task=76 p0=1536
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125097 id_slot=1 id_task=76 p0=2048
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125097 id_slot=1 id_task=76 p0=2560
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125097 id_slot=1 id_task=76 p0=3072
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125097 id_slot=1 id_task=76 p0=3584
INFO [ print_timings] prompt eval time = 1927.38 ms / 3740 tokens ( 0.52 ms per token, 1940.46 tokens per second) | tid="140411292143616" timestamp=1723125099 id_slot=1 id_task=76 t_prompt_processing=1927.375 n_prompt_tokens_processed=3740 t_token=0.5153409090909091 n_tokens_second=1940.463065049614
INFO [ print_timings] generation eval time = 1145.59 ms / 76 runs ( 15.07 ms per token, 66.34 tokens per second) | tid="140411292143616" timestamp=1723125099 id_slot=1 id_task=76 t_token_generation=1145.587 n_decoded=76 t_token=15.073513157894737 n_tokens_second=66.34153495107748
INFO [ print_timings] total time = 3072.96 ms | tid="140411292143616" timestamp=1723125099 id_slot=1 id_task=76 t_prompt_processing=1927.375 t_token_generation=1145.587 t_total=3072.962
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125099 id_slot=1 id_task=76 n_ctx=16128 n_past=3815 n_system_tokens=0 n_cache_tokens=3584 truncated=true
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125099
INFO [ log_server_request] request | tid="140409753817088" timestamp=1723125099 remote_addr="43.153.18.71" remote_port=36190 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125099
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125099 id_slot=2 id_task=161
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125099 id_slot=2 id_task=161 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125099 id_slot=2 id_task=161 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125099 id_slot=2 id_task=161 p0=1024
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125100 id_slot=2 id_task=161 p0=1536
INFO [ print_timings] prompt eval time = 1117.78 ms / 1543 tokens ( 0.72 ms per token, 1380.41 tokens per second) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=161 t_prompt_processing=1117.784 n_prompt_tokens_processed=1543 t_token=0.7244225534672716 n_tokens_second=1380.409810840019
INFO [ print_timings] generation eval time = 14567.23 ms / 906 runs ( 16.08 ms per token, 62.19 tokens per second) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=161 t_token_generation=14567.234 n_decoded=906 t_token=16.07862472406181 n_tokens_second=62.19437403147364
INFO [ print_timings] total time = 15685.02 ms | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=161 t_prompt_processing=1117.784 t_token_generation=14567.234 t_total=15685.018
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=161 n_ctx=16128 n_past=2448 n_system_tokens=0 n_cache_tokens=1536 truncated=false
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125115
INFO [ log_server_request] request | tid="140409762209792" timestamp=1723125115 remote_addr="43.153.18.71" remote_port=36174 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125115
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=1072
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=1072 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=1072 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=1072 p0=1024
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125115 id_slot=2 id_task=1072 p0=1536
INFO [ print_timings] prompt eval time = 1318.40 ms / 1781 tokens ( 0.74 ms per token, 1350.88 tokens per second) | tid="140411292143616" timestamp=1723125123 id_slot=2 id_task=1072 t_prompt_processing=1318.401 n_prompt_tokens_processed=1781 t_token=0.7402588433464347 n_tokens_second=1350.8788297338974
INFO [ print_timings] generation eval time = 7254.65 ms / 450 runs ( 16.12 ms per token, 62.03 tokens per second) | tid="140411292143616" timestamp=1723125123 id_slot=2 id_task=1072 t_token_generation=7254.651 n_decoded=450 t_token=16.121446666666667 n_tokens_second=62.02917273346437
INFO [ print_timings] total time = 8573.05 ms | tid="140411292143616" timestamp=1723125123 id_slot=2 id_task=1072 t_prompt_processing=1318.401 t_token_generation=7254.651 t_total=8573.052
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125123 id_slot=2 id_task=1072 n_ctx=16128 n_past=2230 n_system_tokens=0 n_cache_tokens=1536 truncated=false
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125123
INFO [ log_server_request] request | tid="140409745424384" timestamp=1723125123 remote_addr="43.153.18.71" remote_port=42030 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125123
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125123 id_slot=3 id_task=1527
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125123 id_slot=3 id_task=1527 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125124 id_slot=3 id_task=1527 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125124 id_slot=3 id_task=1527 p0=1024
INFO [ print_timings] prompt eval time = 1365.03 ms / 1534 tokens ( 0.89 ms per token, 1123.78 tokens per second) | tid="140411292143616" timestamp=1723125133 id_slot=3 id_task=1527 t_prompt_processing=1365.034 n_prompt_tokens_processed=1534 t_token=0.8898526727509779 n_tokens_second=1123.7815321816158
INFO [ print_timings] generation eval time = 7954.98 ms / 471 runs ( 16.89 ms per token, 59.21 tokens per second) | tid="140411292143616" timestamp=1723125133 id_slot=3 id_task=1527 t_token_generation=7954.977 n_decoded=471 t_token=16.889547770700638 n_tokens_second=59.208216441103474
INFO [ print_timings] total time = 9320.01 ms | tid="140411292143616" timestamp=1723125133 id_slot=3 id_task=1527 t_prompt_processing=1365.034 t_token_generation=7954.977 t_total=9320.011
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125133 id_slot=3 id_task=1527 n_ctx=16128 n_past=2004 n_system_tokens=0 n_cache_tokens=1024 truncated=false
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125133
INFO [ log_server_request] request | tid="140409745424384" timestamp=1723125133 remote_addr="43.153.18.71" remote_port=42030 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125133
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125133 id_slot=0 id_task=2002
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125133 id_slot=0 id_task=2002 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125133 id_slot=0 id_task=2002 p0=512
INFO [ print_timings] prompt eval time = 907.58 ms / 906 tokens ( 1.00 ms per token, 998.26 tokens per second) | tid="140411292143616" timestamp=1723125135 id_slot=0 id_task=2002 t_prompt_processing=907.579 n_prompt_tokens_processed=906 t_token=1.001742825607064 n_tokens_second=998.2602065495125
INFO [ print_timings] generation eval time = 1150.37 ms / 68 runs ( 16.92 ms per token, 59.11 tokens per second) | tid="140411292143616" timestamp=1723125135 id_slot=0 id_task=2002 t_token_generation=1150.367 n_decoded=68 t_token=16.91716176470588 n_tokens_second=59.11157048142028
INFO [ print_timings] total time = 2057.95 ms | tid="140411292143616" timestamp=1723125135 id_slot=0 id_task=2002 t_prompt_processing=907.579 t_token_generation=1150.367 t_total=2057.946
INFO [ update_slots] slot released | tid="140411292143616" timestamp=1723125135 id_slot=0 id_task=2002 n_ctx=16128 n_past=973 n_system_tokens=0 n_cache_tokens=512 truncated=false
INFO [ update_slots] all slots are idle | tid="140411292143616" timestamp=1723125135
INFO [ log_server_request] request | tid="140409745424384" timestamp=1723125135 remote_addr="43.153.18.71" remote_port=42030 status=200 method="POST" path="/v1/chat/completions" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="140411292143616" timestamp=1723125135 id_slot=1 id_task=2072
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125135 id_slot=1 id_task=2072 p0=0
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125135 id_slot=1 id_task=2072 p0=512
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125136 id_slot=1 id_task=2072 p0=1024
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125136 id_slot=1 id_task=2072 p0=1536
INFO [ update_slots] kv cache rm [p0, end) | tid="140411292143616" timestamp=1723125137 id_slot=1 id_task=2072 p0=2048
^C^CReceived second interrupt, terminating immediately.
can you try with --ctx-size 16384 instead of --ctx-size 16128 ? (I'm not sure if it fixes the problem or not)
It does not work with --ctx-size 16384 ,but If I set like this : --ctx-size 32000 ,It works, I think it is related about the truncated process is enabled .How could I disabled the truncated process. THANKS ！
I'm not sure what you mean by "truncated process".
Keep in mind that the actual context size will be --ctx-size divided by --parallel, so for example with 16384 you have 16384 / 4096 = 4096 tokens per slot, so it's normal to increase ctx size if you set a high value for --parallel
This issue was closed because it has been inactive for 14 days since being marked as stale.
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