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Facico avatar Facico commented on July 16, 2024

@greatewei 可以参考我们的tool readme,里面介绍了如何使用gptq量化运行

from chinese-vicuna.

greatewei avatar greatewei commented on July 16, 2024

@greatewei 可以参考我们的tool readme,里面介绍了如何使用gptq量化运行

嗯,我成功训练了量化模型,但是在第三步执行 generate_quant.py文件发生了错误,缺少了gptq模块

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Facico avatar Facico commented on July 16, 2024

我们在tool readme中Quantize LLaMA第二行,第二句话“运行下面的代码前,你需要用 pip install gptq>=0.0.2 命令来安装 gptq。”讲了如何安装gptq

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greatewei avatar greatewei commented on July 16, 2024

我们在tool readme中Quantize LLaMA第二行,第二句话“运行下面的代码前,你需要用 pip install gptq>=0.0.2 命令来安装 gptq。”讲了如何安装gptq

看到了,感谢!

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greatewei avatar greatewei commented on July 16, 2024

@Facico 你好,我遇到了一个问题,generate_quant.py脚本执行量化脚本后,效果很差,如图:
image
我的量化过程如下:

  1. 13b-lora 与 llama13b进行合并生成一个新的模型 chinese-v-13b-hf, 这个模型测试过,能够正常的交流。
  2. 执行命令 python tools/llama_quant.py /data/chat/models/chinese-v-13b-hf ptb --wbits 4 --groupsize 128 --save /data/chat/models/chinese-v-13b-hf/pyllama-4b.pt 进行了模型量化,最终输出了 pyllama-4b.pt文件
  3. 执行命令python tools/generate_quant.py --model_path "/data/chat/models/chinese-v-13b-hf" --quant_path "/data/chat/models/chinese-v-13b-hf/pyllama-4b.pt" --wbits 4

是不是哪个环节出了错误

from chinese-vicuna.

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