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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 |
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[2024-06-06 21:59:28] INFO auto_config.py:116: [92mFound[0m model configuration: /models/Mistral-7B-Instruct-v0.3/config.json |
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[2024-06-06 21:59:28] INFO auto_config.py:154: [92mFound[0m model type: [1mmistral[0m. Use `--model-type` to override. |
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[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) |
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[2024-06-06 21:59:28] INFO mistral_model.py:88: [1mprefill_chunk_size[0m defaults to 2048 |
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[2024-06-06 21:59:28] INFO gen_config.py:143: [generation_config.json] Setting [1mbos_token_id[0m: 1 |
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[2024-06-06 21:59:28] INFO gen_config.py:143: [generation_config.json] Setting [1meos_token_id[0m: 2 |
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[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 |
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[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 |
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[2024-06-06 21:59:28] INFO gen_config.py:157: [91mNot found[0m tokenizer config: /models/Mistral-7B-Instruct-v0.3/vocab.json |
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[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 |
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[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} |
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[2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mpad_token_id[0m: 0 |
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[2024-06-06 21:59:28] INFO gen_config.py:32: [System default] Setting [1mpresence_penalty[0m: 0.0 |
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[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 |
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/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 |
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[2024-06-06 21:59:30] INFO auto_config.py:116: [92mFound[0m model configuration: /models/Mistral-7B-Instruct-v0.3/config.json |
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[2024-06-06 21:59:38] INFO auto_device.py:35: Using device: [1mcuda:0[0m |
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[2024-06-06 21:59:38] INFO auto_weight.py:71: Finding weights in: /models/Mistral-7B-Instruct-v0.3 |
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[2024-06-06 21:59:38] INFO auto_weight.py:137: [91mNot found[0m Huggingface PyTorch |
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[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 |
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[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. |
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[2024-06-06 21:59:38] INFO auto_weight.py:111: Using source weight format: [1mhuggingface-safetensor[0m. Use `--source-format` to override. |
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[2024-06-06 21:59:38] INFO auto_config.py:154: [92mFound[0m model type: [1mmistral[0m. Use `--model-type` to override. |
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[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) |
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[2024-06-06 21:59:38] INFO mistral_model.py:88: [1mprefill_chunk_size[0m defaults to 2048 |
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[1mWeight conversion with arguments:[0m |
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[1m--config[0m /models/Mistral-7B-Instruct-v0.3/config.json |
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[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) |
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[1m--model-type[0m mistral |
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[1m--device[0m cuda:0 |
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[1m--output[0m /models/mlc-delivery/hf/mlc-ai/Mistral-7B-Instruct-v0.3-q3f16_1-MLC |
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[2024-06-06 22:00:27] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.6.mlp.gate_up_proj.q_weight[0m", shape: (28672, 412), dtype: uint32 |
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[2024-06-06 22:00:27] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.6.mlp.gate_up_proj.q_scale[0m", shape: (28672, 103), dtype: float16 |
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[2024-06-06 22:00:30] INFO huggingface_loader.py:167: [Quantized] Parameter: "[1mmodel.layers.8.mlp.gate_up_proj.q_weight[0m", shape: (28672, 412), dtype: uint32 |
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[2024-06-06 22:00:51] INFO huggingface_loader.py:197: Unloading HF weight file: /models/Mistral-7B-Instruct-v0.3/model-00002-of-00003.safetensors |
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[2024-06-06 22:00:52] INFO stats.py:77: [92mTime usage[0m: HF loading: 21.882 sec; Pre-quantization mapping: 36.046 sec; Quantization: 3.279 sec |
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[2024-06-06 22:00:52] INFO stats.py:91: [92mRAM usage[0m: Peak RAM: 9.313 GB. Total bytes loaded from disk: 27.001 GB |
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[2024-06-06 22:00:52] INFO convert_weight.py:155: [92mParameter size[0m after quantization: 3.052 GB |
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[2024-06-06 22:00:52] INFO convert_weight.py:160: [92mTotal parameters[0m: 7,248,023,552 |
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[2024-06-06 22:00:52] INFO convert_weight.py:161: [92mBits per parameter[0m: 3.618 |
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[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 |
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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 |
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