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/opt/conda/envs/py310/bin/python -m mlc_llm gen_config /models/Mistral-7B-Instruct-v0.3 --quantization q3f16_1 --conv-template mistral_default --output /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC [2024-06-06 21:59:28] INFO auto_config.py:116: [92mFound[0m model configuration: /models/Mistral-7B-Instruct-v0.3/config.json [2024-06-06 21:59:28] INFO auto_config.py:154: [92mFound[0m model type: [1mmistral[0m. Use `--model-type` to override. [2024-06-06 21:59:28] INFO mistral_model.py:59: [1mcontext_window_size[0m not found in config.json. Falling back to [1mmax_position_embeddings[0m (32768) [2024-06-06 21:59:28] INFO mistral_model.py:88: [1mprefill_chunk_size[0m defaults to 2048 [2024-06-06 21:59:28] INFO config.py:107: Overriding [1mmax_batch_size[0m from 1 to 80 [2024-06-06 21:59:28] INFO gen_config.py:143: [generation_config.json] Setting [1mbos_token_id[0m: 1 [2024-06-06 21:59:28] INFO gen_config.py:143: [generation_config.json] Setting [1meos_token_id[0m: 2 [2024-06-06 21:59:28] INFO gen_config.py:155: [92mFound[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/tokenizer.model. Copying to [1m/models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC/tokenizer.model[0m [2024-06-06 21:59:28] INFO gen_config.py:155: [92mFound[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/tokenizer.json. Copying to [1m/models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC/tokenizer.json[0m [2024-06-06 21:59:28] INFO gen_config.py:157: [91mNot found[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/vocab.json [2024-06-06 21:59:28] INFO gen_config.py:157: [91mNot found[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/merges.txt [2024-06-06 21:59:28] INFO gen_config.py:157: [91mNot found[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/added_tokens.json [2024-06-06 21:59:28] INFO gen_config.py:155: [92mFound[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/tokenizer_config.json. Copying to [1m/models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC/tokenizer_config.json[0m [2024-06-06 21:59:28] INFO gen_config.py:216: Detected tokenizer info: {'token_postproc_method': 'byte_fallback', 'prepend_space_in_encode': False, 'strip_space_in_decode': True} [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mpad_token_id[0m: 0 [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mtemperature[0m: 1.0 [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mpresence_penalty[0m: 0.0 [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mfrequency_penalty[0m: 0.0 [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mrepetition_penalty[0m: 1.0 [2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mtop_p[0m: 1.0 [2024-06-06 21:59:28] INFO gen_config.py:223: Dumping configuration file to: [1m/models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC/mlc-chat-config.json[0m /opt/conda/envs/py310/bin/python -m mlc_llm convert_weight /models/Mistral-7B-Instruct-v0.3 --quantization q3f16_1 --output /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC [2024-06-06 21:59:30] INFO auto_config.py:116: [92mFound[0m model configuration: /models/Mistral-7B-Instruct-v0.3/config.json [2024-06-06 21:59:31] INFO auto_device.py:79: [92mFound[0m device: cuda:0 [2024-06-06 21:59:33] INFO auto_device.py:88: [91mNot found[0m device: rocm:0 [2024-06-06 21:59:34] INFO auto_device.py:88: [91mNot found[0m device: metal:0 [2024-06-06 21:59:36] INFO auto_device.py:79: [92mFound[0m device: vulkan:0 [2024-06-06 21:59:36] INFO auto_device.py:79: [92mFound[0m device: vulkan:1 [2024-06-06 21:59:36] INFO auto_device.py:79: [92mFound[0m device: vulkan:2 [2024-06-06 21:59:36] INFO auto_device.py:79: [92mFound[0m device: vulkan:3 [2024-06-06 21:59:38] INFO auto_device.py:88: [91mNot found[0m device: opencl:0 [2024-06-06 21:59:38] INFO auto_device.py:35: Using device: [1mcuda:0[0m [2024-06-06 21:59:38] INFO auto_weight.py:71: Finding weights in: /models/Mistral-7B-Instruct-v0.3 [2024-06-06 21:59:38] INFO auto_weight.py:137: [91mNot found[0m Huggingface PyTorch [2024-06-06 21:59:38] INFO auto_weight.py:144: [92mFound[0m source weight format: huggingface-safetensor. Source configuration: /models/Mistral-7B-Instruct-v0.3/model.safetensors.index.json [2024-06-06 21:59:38] INFO auto_weight.py:107: Using source weight configuration: [1m/models/Mistral-7B-Instruct-v0.3/model.safetensors.index.json[0m. Use `--source` to override. [2024-06-06 21:59:38] INFO auto_weight.py:111: Using source weight format: [1mhuggingface-safetensor[0m. Use `--source-format` to override. [2024-06-06 21:59:38] INFO auto_config.py:154: [92mFound[0m model type: [1mmistral[0m. Use `--model-type` to override. [2024-06-06 21:59:38] INFO mistral_model.py:59: [1mcontext_window_size[0m not found in config.json. Falling back to [1mmax_position_embeddings[0m (32768) [2024-06-06 21:59:38] INFO mistral_model.py:88: [1mprefill_chunk_size[0m defaults to 2048 [1mWeight conversion with arguments:[0m [1m--config[0m /models/Mistral-7B-Instruct-v0.3/config.json [1m--quantization[0m GroupQuantize(name='q3f16_1', kind='group-quant', group_size=40, quantize_dtype='int3', storage_dtype='uint32', model_dtype='float16', linear_weight_layout='NK', quantize_embedding=True, quantize_final_fc=True, num_elem_per_storage=10, num_storage_per_group=4, max_int_value=3) [1m--model-type[0m mistral [1m--device[0m cuda:0 [1m--source[0m /models/Mistral-7B-Instruct-v0.3/model.safetensors.index.json [1m--source-format[0m huggingface-safetensor [1m--output[0m /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC Start storing to cache /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC 0%| | 0/195 [00:00<?, ?it/s] [2024-06-06 21:59:40] INFO huggingface_loader.py:185: Loading HF parameters from: 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1%| | 1/195 [00:12<37:48, 11.69s/it] [2024-06-06 21:59:53] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.22.mlp.down_proj.q_weight[0m", shape: (4096, 1436), dtype: uint32 1%| | 1/195 [00:12<37:48, 11.69s/it] [2024-06-06 21:59:53] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.22.mlp.down_proj.q_scale[0m", shape: (4096, 359), dtype: float16 1%| | 1/195 [00:12<37:48, 11.69s/it] 2%|▏ | 3/195 [00:12<11:11, 3.50s/it] [2024-06-06 21:59:54] INFO group_quantization.py:217: Compiling quantize function for key: ((28672, 4096), float16, cuda, axis=1, output_transpose=False) 2%|▏ | 3/195 [00:14<11:11, 3.50s/it] [2024-06-06 21:59:55] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.22.mlp.gate_up_proj.q_weight[0m", shape: (28672, 412), dtype: uint32 2%|▏ | 3/195 [00:15<11:11, 3.50s/it] [2024-06-06 21:59:55] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.22.mlp.gate_up_proj.q_scale[0m", shape: (28672, 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Total bytes loaded from disk: 27.001 GB [2024-06-06 22:00:52] INFO convert_weight.py:155: [92mParameter size[0m after quantization: 3.052 GB [2024-06-06 22:00:52] INFO convert_weight.py:160: [92mTotal parameters[0m: 7,248,023,552 [2024-06-06 22:00:52] INFO convert_weight.py:161: [92mBits per parameter[0m: 3.618 [2024-06-06 22:00:52] INFO convert_weight.py:166: Saved to directory: [1m/models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC[0m All finished, 98 total shards committed, record saved to /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC/ndarray-cache.json |