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shizhediao committed Apr 2, 2023
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[![Embark](https://img.shields.io/badge/discord-LMFlow-%237289da.svg?logo=discord)](https://discord.gg/srGxyazbNs)
[![WeChat badge](https://img.shields.io/badge/微信-加入-brightgreen?logo=wechat&amp)](https://i.328888.xyz/2023/04/02/iHtF23.png)
[![slack badge](https://img.shields.io/badge/Slack-join-blueviolet?logo=slack&amp)](https://join.slack.com/t/lmflow/shared_invite/zt-1s6egx12s-THlwHuCjF6~JGKmx7JoJPA)
[![colab badge](https://img.shields.io/badge/Colab-(shell)%20%20chatbot:%20gpt--neo-orange?logo=google-colab&amp)](https://colab.research.google.com/drive/1P9Hf6_mLE7WHH92pw73j9D5kz6GTdkow?usp=sharing)


An extensible, convenient, and efficient toolbox for finetuning large machine learning models, designed to be user-friendly, speedy and reliable, and accessible to the entire community.

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<img src="https://contrib.rocks/image?repo=OptimalScale/LMFlow" />
</a>


## Citation
If you find this repository useful, please consider giving ⭐ and citing:

```
@misc{lmflow,
author = {Shizhe Diao and Rui Pan and Hanze Dong and KaShun Shum and Jipeng Zhang and Wei Xiong and Tong Zhang},
title = {LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://optimalscale.github.io/LMFlow/}},
}
```

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