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@@ -12,27 +12,6 @@ license: apache-2.0
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  ```
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- ### Script to AWQ quantization
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- ```
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- from awq import AutoAWQForCausalLM
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- from transformers import AutoTokenizer
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-
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- model_path = 'PATH_TO Poro-34B'
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- quant_path = 'Poro-34B-AWQ'
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- quant_config = { "zero_point": True, "q_group_size": 128, "w_bit": 4, "version": "GEMM" }
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-
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- # Load model
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- model = AutoAWQForCausalLM.from_pretrained(model_path, safetensors=True)
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- tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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-
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- # Quantize
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- model.quantize(tokenizer, quant_config=quant_config)
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-
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- # Save quantized model
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- model.save_quantized(quant_path)
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- tokenizer.save_pretrained(quant_path)
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- ```
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-
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  ### Generate
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  ```
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  from awq import AutoAWQForCausalLM
 
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  ```
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  ### Generate
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  ```
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  from awq import AutoAWQForCausalLM