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ChatGLM-6B
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Add instructions for installing Git LFS

pull/150/merge
duzx16 2023-03-29 23:24:33 +08:00
parent fc55c075fe
commit 323ce7c865
2 changed files with 18 additions and 3 deletions
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@ -160,8 +160,9 @@ model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4",trust_remote_code=True
如果遇到了报错 `Could not find module 'nvcuda.dll'` 或者 `RuntimeError: Unknown platform: darwin` (MacOS) 的话请参考这个[Issue](https://github.com/THUDM/ChatGLM-6B/issues/6#issuecomment-1470060041).
### Mac 上的 GPU 加速
对于搭载了Apple Silicon的Mac（以及MacBook），可以使用 MPS 后端来在 GPU 上运行 ChatGLM-6B。首先需要参考 Apple 的 [官方说明](https://developer.apple.com/metal/pytorch) 安装 PyTorch-Nightly。然后将模型仓库 clone 到本地
对于搭载了Apple Silicon的Mac（以及MacBook），可以使用 MPS 后端来在 GPU 上运行 ChatGLM-6B。首先需要参考 Apple 的 [官方说明](https://developer.apple.com/metal/pytorch) 安装 PyTorch-Nightly。然后将模型仓库 clone 到本地（需要先[安装Git LFS](https://docs.github.com/zh/repositories/working-with-files/managing-large-files/installing-git-large-file-storage)）
```shell
git lfs install
git clone https://huggingface.co/THUDM/chatglm-6b
```
将代码中的模型加载改为从本地加载，并使用 mps 后端

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README_en.md
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@ -9,7 +9,7 @@ ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese QA and dial
Try the [online demo](https://huggingface.co/spaces/ysharma/ChatGLM-6b_Gradio_Streaming) on Huggingface Spaces.
## Update
**[2023/03/23]** Add API deployment, thanks to [@LemonQu-GIT](https://github.com/LemonQu-GIT). Add embedding-quantized model [ChatGLM-6B-INT4-QE](https://huggingface.co/THUDM/chatglm-6b-int4-qe)
**[2023/03/23]** Add API deployment, thanks to [@LemonQu-GIT](https://github.com/LemonQu-GIT). Add embedding-quantized model [ChatGLM-6B-INT4-QE](https://huggingface.co/THUDM/chatglm-6b-int4-qe). Add support for GPU inference on Mac with Apple Silicon.
**[2023/03/19]** Add streaming output function `stream_chat`, already applied in web and CLI demo. Fix Chinese punctuations in output. Add quantized model [ChatGLM-6B-INT4](https://huggingface.co/THUDM/chatglm-6b-int4).
@ -154,7 +154,21 @@ model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).fl
model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True).float()
```
**For Mac users**: if your encounter the error `RuntimeError: Unknown platform: darwin`, please refer to this [Issue](https://github.com/THUDM/ChatGLM-6B/issues/6#issuecomment-1470060041).
If your encounter the error `Could not find module 'nvcuda.dll'` or `RuntimeError: Unknown platform: darwin`(MacOS), please refer to this [Issue](https://github.com/THUDM/ChatGLM-6B/issues/6#issuecomment-1470060041).
### GPU Inference on Mac
For Macs (and MacBooks) with Apple Silicon, it is possible to use the MPS backend to run ChatGLM-6B on the GPU. First, you need to refer to Apple's [official instructions](https://developer.apple.com/metal/pytorch) to install PyTorch-Nightly. Then clone the model repository locally (you need to [install Git LFS](https://docs.github.com/zh/repositories/working-with-files/managing-large-files/installing-git-large-file-storage)）
```shell
git lfs install
git clone https://huggingface.co/THUDM/chatglm-6b
```
Change the code to load the model from your local path, and use the mps backend:
```python
model = AutoModel.from_pretrained("your local path", trust_remote_code=True).half().to('mps')
```
Then you can use GPU-accelerated model inference on Mac.
## ChatGLM-6B Examples