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---
language:
- zh
- en
tags:
- chatglm
- glm
- onnx
- onnxruntime
---
# ChatGLM-6B + ONNX
This model is exported from [ChatGLM-6b](https://huggingface.co/THUDM/chatglm-6b) with int8 quantization and optimized for [ONNXRuntime](https://onnxruntime.ai/) inference. Export code in [this repo](https://github.com/K024/chatglm-q).
Inference code with ONNXRuntime is uploaded with the model. Install requirements and run `streamlit run web-ui.py` to start chatting. Currently the `MatMulInteger` (for u8s8 data type) and `DynamicQuantizeLinear` operators are only supported on CPU. Arm64 with Neon support (Apple M1/M2) should be reasonably fast.
安装依赖并运行 `streamlit run web-ui.py` 预览模型效果。由于 ONNXRuntime 算子支持问题,目前仅能够使用 CPU 进行推理,在 Arm64 (Apple M1/M2) 上有可观的速度。具体的 ONNX 导出代码在[这个仓库](https://github.com/K024/chatglm-q)中。
## Usage
Clone with [git-lfs](https://git-lfs.com/):
```sh
git lfs clone https://huggingface.co/K024/ChatGLM-6b-onnx-u8s8
cd ChatGLM-6b-onnx-u8s8
pip install -r requirements.txt
streamlit run web-ui.py
```
Or use `huggingface_hub` [python client lib](https://huggingface.co/docs/huggingface_hub/guides/download#download-files-to-local-folder) to download the repo snapshot:
```python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="K024/ChatGLM-6b-onnx-u8s8", local_dir="./ChatGLM-6b-onnx-u8s8")
```
Codes are released under MIT license.
Model weights are released under the same license as ChatGLM-6b, see [MODEL LICENSE](https://huggingface.co/THUDM/chatglm-6b/blob/main/MODEL_LICENSE).