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修改了awq的量化readme

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刘丹 2024-06-27 09:42:20 +08:00
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1 changed files with 7 additions and 4 deletions
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@ -312,11 +312,14 @@ print(model.response("<用户>山东省最高的山是哪座山, 它比黄山高
custom_data=[{'question':'过敏性鼻炎有什么症状？','answer':'过敏性鼻炎可能鼻塞，流鼻涕，头痛等症状反复发作，严重时建议及时就医。'}, custom_data=[{'question':'过敏性鼻炎有什么症状？','answer':'过敏性鼻炎可能鼻塞，流鼻涕，头痛等症状反复发作，严重时建议及时就医。'},
{'question':'1+1等于多少？','answer':'等于2'}] {'question':'1+1等于多少？','answer':'等于2'}]
``` ```
4. 根据选择的数据集，修改quantize/awq_quantize.py 第三十八行： 4. 根据选择的数据集，修改quantize/awq_quantize.py 为以下三行代码其中一行：
```python ```python
model.quantize(tokenizer, quant_config=quant_config, calib_data=load_wikitext(quant_data_path=quant_data_path))#使用wikitext进行量化 #使用wikitext进行量化
model.quantize(tokenizer, quant_config=quant_config, calib_data=load_alpaca(quant_data_path=quant_data_path))#使用alpaca进行量化 model.quantize(tokenizer, quant_config=quant_config, calib_data=load_wikitext(quant_data_path=quant_data_path))
model.quantize(tokenizer, quant_config=quant_config, calib_data=load_cust_data(quant_data_path=quant_data_path))#使用自定义数据集进行量化 #使用alpaca进行量化
model.quantize(tokenizer, quant_config=quant_config, calib_data=load_alpaca(quant_data_path=quant_data_path))
#使用自定义数据集进行量化
model.quantize(tokenizer, quant_config=quant_config, calib_data=load_cust_data(quant_data_path=quant_data_path))
``` ```
5. 运行quantize/awq_quantize.py文件,在设置的quan_path目录下可得awq量化后的模型。 5. 运行quantize/awq_quantize.py文件,在设置的quan_path目录下可得awq量化后的模型。