Comments (7)
可能是你直接pip install -r requirements.txt导致的torch不可用。
你检查下torch能不能用,或者启动模型时是不是有CUDA extension not installed.
我重新配了个环境解决了:
1.把requirements.txt里的torch那行去掉。
2.找对应你CUDA版本的pytorch版本,比如我cuda11.8.我看到gptq最低支持到pytorch2.1.0。
3.下面是我所有的安装命令:
conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia
(https://pytorch.org/get-started/previous-versions/)
pip install -r requirements.txt
(txt已经去掉了torch)
pip install auto-gptq==0.5.1 --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
(https://github.com/AutoGPTQ/AutoGPTQ/blob/main/docs/INSTALLATION.md)
pip install --upgrade transformers optimum
(因为这里显示我没有optimum库,一起把这俩更新保证兼容)
然后我就发现比之前快的多
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@zxdposter 你好请问34B inference需要几张显卡?需要多卡吗?
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same too. 8x 4090 . so slow.
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你好,请问你的gptq版本是多少,官网没看到针对pytorch2.1.2的autogptq版本耶
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@lyan62 大概需要20-30G显存
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确实太慢了,有什么好的方法吗
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可能是你直接pip install -r requirements.txt导致的torch不可用。 你检查下torch能不能用,或者启动模型时是不是有CUDA extension not installed. 我重新配了个环境解决了: 1.把requirements.txt里的torch那行去掉。 2.找对应你CUDA版本的pytorch版本,比如我cuda11.8.我看到gptq最低支持到pytorch2.1.0。 3.下面是我所有的安装命令: conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia (https://pytorch.org/get-started/previous-versions/) pip install -r requirements.txt (txt已经去掉了torch) pip install auto-gptq==0.5.1 --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/ (https://github.com/AutoGPTQ/AutoGPTQ/blob/main/docs/INSTALLATION.md) pip install --upgrade transformers optimum (因为这里显示我没有optimum库,一起把这俩更新保证兼容) 然后我就发现比之前快的多
@ChinesePainting 感谢提供解决方法,后续我尝试一下。
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