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 /opt/conda/envs/py310/bin/python -m mlc_llm gen_config /models/Meta-Llama-3-8B-Instruct --quantization q4f16_1 --conv-template llama-3 --output /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC
[2024-06-04 03:16:55] INFO auto_config.py:116: Found model configuration: /models/Meta-Llama-3-8B-Instruct/config.json
[2024-06-04 03:16:55] INFO auto_config.py:154: Found model type: llama. Use `--model-type` to override.
[2024-06-04 03:16:55] INFO llama_model.py:52: context_window_size not found in config.json. Falling back to max_position_embeddings (8192)
[2024-06-04 03:16:55] INFO llama_model.py:72: prefill_chunk_size defaults to 2048
[2024-06-04 03:16:55] INFO config.py:107: Overriding max_batch_size from 1 to 80
[2024-06-04 03:16:55] INFO gen_config.py:143: [generation_config.json] Setting bos_token_id: 128000
[2024-06-04 03:16:55] INFO gen_config.py:143: [generation_config.json] Setting eos_token_id: [128001, 128009]
[2024-06-04 03:16:55] INFO gen_config.py:143: [generation_config.json] Setting temperature: 0.6
[2024-06-04 03:16:55] INFO gen_config.py:143: [generation_config.json] Setting top_p: 0.9
[2024-06-04 03:16:55] INFO gen_config.py:157: Not found tokenizer config: /models/Meta-Llama-3-8B-Instruct/tokenizer.model
[2024-06-04 03:16:55] INFO gen_config.py:155: Found tokenizer config: /models/Meta-Llama-3-8B-Instruct/tokenizer.json. Copying to /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC/tokenizer.json
[2024-06-04 03:16:55] INFO gen_config.py:157: Not found tokenizer config: /models/Meta-Llama-3-8B-Instruct/vocab.json
[2024-06-04 03:16:55] INFO gen_config.py:157: Not found tokenizer config: /models/Meta-Llama-3-8B-Instruct/merges.txt
[2024-06-04 03:16:55] INFO gen_config.py:157: Not found tokenizer config: /models/Meta-Llama-3-8B-Instruct/added_tokens.json
[2024-06-04 03:16:55] INFO gen_config.py:155: Found tokenizer config: /models/Meta-Llama-3-8B-Instruct/tokenizer_config.json. Copying to /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC/tokenizer_config.json
[2024-06-04 03:16:55] INFO gen_config.py:216: Detected tokenizer info: {'token_postproc_method': 'byte_level', 'prepend_space_in_encode': False, 'strip_space_in_decode': False}
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting pad_token_id: 0
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting presence_penalty: 0.0
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting frequency_penalty: 0.0
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting repetition_penalty: 1.0
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting mean_gen_len: 128
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting max_gen_len: 512
[2024-06-04 03:16:55] INFO gen_config.py:32: [System default] Setting shift_fill_factor: 0.3
[2024-06-04 03:16:55] INFO gen_config.py:223: Dumping configuration file to: /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC/mlc-chat-config.json
/opt/conda/envs/py310/bin/python -m mlc_llm convert_weight /models/Meta-Llama-3-8B-Instruct --quantization q4f16_1 --output /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC
[2024-06-04 03:16:56] INFO auto_config.py:116: Found model configuration: /models/Meta-Llama-3-8B-Instruct/config.json
[2024-06-04 03:16:58] INFO auto_device.py:79: Found device: cuda:0
[2024-06-04 03:16:59] INFO auto_device.py:88: Not found device: rocm:0
[2024-06-04 03:17:01] INFO auto_device.py:88: Not found device: metal:0
[2024-06-04 03:17:02] INFO auto_device.py:79: Found device: vulkan:0
[2024-06-04 03:17:02] INFO auto_device.py:79: Found device: vulkan:1
[2024-06-04 03:17:02] INFO auto_device.py:79: Found device: vulkan:2
[2024-06-04 03:17:02] INFO auto_device.py:79: Found device: vulkan:3
[2024-06-04 03:17:04] INFO auto_device.py:88: Not found device: opencl:0
[2024-06-04 03:17:04] INFO auto_device.py:35: Using device: cuda:0
[2024-06-04 03:17:04] INFO auto_weight.py:71: Finding weights in: /models/Meta-Llama-3-8B-Instruct
[2024-06-04 03:17:04] INFO auto_weight.py:137: Not found Huggingface PyTorch
[2024-06-04 03:17:04] INFO auto_weight.py:144: Found source weight format: huggingface-safetensor. Source configuration: /models/Meta-Llama-3-8B-Instruct/model.safetensors.index.json
[2024-06-04 03:17:04] INFO auto_weight.py:107: Using source weight configuration: /models/Meta-Llama-3-8B-Instruct/model.safetensors.index.json. Use `--source` to override.
[2024-06-04 03:17:04] INFO auto_weight.py:111: Using source weight format: huggingface-safetensor. Use `--source-format` to override.
[2024-06-04 03:17:04] INFO auto_config.py:154: Found model type: llama. Use `--model-type` to override.
[2024-06-04 03:17:04] INFO llama_model.py:52: context_window_size not found in config.json. Falling back to max_position_embeddings (8192)
[2024-06-04 03:17:04] INFO llama_model.py:72: prefill_chunk_size defaults to 2048
Weight conversion with arguments:
--config /models/Meta-Llama-3-8B-Instruct/config.json
--quantization GroupQuantize(name='q4f16_1', kind='group-quant', group_size=32, quantize_dtype='int4', storage_dtype='uint32', model_dtype='float16', linear_weight_layout='NK', quantize_embedding=True, quantize_final_fc=True, num_elem_per_storage=8, num_storage_per_group=4, max_int_value=7)
--model-type llama
--device cuda:0
--source /models/Meta-Llama-3-8B-Instruct/model.safetensors.index.json
--source-format huggingface-safetensor
--output /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC
Start storing to cache /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC
0%| | 0/195 [00:00<?, ?it/s] [2024-06-04 03:17:07] INFO huggingface_loader.py:185: Loading HF parameters from: /models/Meta-Llama-3-8B-Instruct/model-00004-of-00004.safetensors
0%| | 0/195 [00:00<?, ?it/s] [2024-06-04 03:17:11] INFO group_quantization.py:217: Compiling quantize function for key: ((128256, 4096), float16, cuda, axis=1, output_transpose=False)
0%| | 0/195 [00:03<?, ?it/s] [2024-06-04 03:17:12] INFO huggingface_loader.py:167: [Quantized] Parameter: "lm_head.q_weight", shape: (128256, 512), dtype: uint32
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1%| | 1/195 [00:05<17:57, 5.55s/it] [2024-06-04 03:17:14] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.31.mlp.down_proj.q_weight", shape: (4096, 1792), dtype: uint32
1%| | 1/195 [00:06<17:57, 5.55s/it] [2024-06-04 03:17:14] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.31.mlp.down_proj.q_scale", shape: (4096, 448), dtype: float16
1%| | 1/195 [00:06<17:57, 5.55s/it] 2%|▏ | 3/195 [00:06<05:36, 1.75s/it] [2024-06-04 03:17:14] INFO huggingface_loader.py:175: [Not quantized] Parameter: "model.layers.31.post_attention_layernorm.weight", shape: (4096,), dtype: float16
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2%|▏ | 3/195 [00:06<05:36, 1.75s/it] [2024-06-04 03:17:20] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.embed_tokens.q_weight", shape: (128256, 512), dtype: uint32
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2%|▏ | 3/195 [00:13<05:36, 1.75s/it] 3%|▎ | 6/195 [00:13<06:40, 2.12s/it] [2024-06-04 03:17:21] INFO huggingface_loader.py:175: [Not quantized] Parameter: "model.layers.0.input_layernorm.weight", shape: (4096,), dtype: float16
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3%|▎ | 6/195 [00:13<06:40, 2.12s/it] 4%|▍ | 8/195 [00:13<04:20, 1.40s/it] [2024-06-04 03:17:22] INFO group_quantization.py:217: Compiling quantize function for key: ((28672, 4096), float16, cuda, axis=1, output_transpose=False)
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4%|▍ | 8/195 [00:14<04:20, 1.40s/it] 5%|▍ | 9/195 [00:14<04:09, 1.34s/it] [2024-06-04 03:17:22] INFO huggingface_loader.py:175: [Not quantized] Parameter: "model.layers.0.post_attention_layernorm.weight", shape: (4096,), dtype: float16
5%|▍ | 9/195 [00:14<04:09, 1.34s/it] [2024-06-04 03:17:22] INFO group_quantization.py:217: Compiling quantize function for key: ((6144, 4096), float16, cuda, axis=1, output_transpose=False)
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[2024-06-04 03:18:15] INFO huggingface_loader.py:197: Unloading HF weight file: /models/Meta-Llama-3-8B-Instruct/model-00002-of-00004.safetensors
[2024-06-04 03:18:15] INFO huggingface_loader.py:197: Unloading HF weight file: /models/Meta-Llama-3-8B-Instruct/model-00003-of-00004.safetensors
[2024-06-04 03:18:16] INFO stats.py:77: Time usage: HF loading: 15.874 sec; Pre-quantization mapping: 35.958 sec; Quantization: 3.089 sec
[2024-06-04 03:18:16] INFO stats.py:91: RAM usage: Peak RAM: 18.469 GB. Total bytes loaded from disk: 29.915 GB
[2024-06-04 03:18:16] INFO convert_weight.py:155: Parameter size after quantization: 4.207 GB
[2024-06-04 03:18:16] INFO convert_weight.py:160: Total parameters: 8,030,261,248
[2024-06-04 03:18:16] INFO convert_weight.py:161: Bits per parameter: 4.500
[2024-06-04 03:18:16] INFO convert_weight.py:166: Saved to directory: /models/mlc-delivery/hf/mlc-ai/Llama-3-8B-Instruct-q4f16_1-MLC
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