README.md

---
title: README
emoji: 🏃
colorFrom: pink
colorTo: red
sdk: static
pinned: false
---

<p align="center" width="100%">
</p>

<div id="top" align="center">

<p style="font-size: 40px; font-weight: bold;">Knowledge Fusion of Large Language Models</p>


<h4> |<a href="https://arxiv.org/abs/2401.10491"> 📑 FuseLLM Paper @ICLR2024 </a> |
<!-- <a href="https://arxiv.org/abs/2402.16107"> 📑 FuseChat Tech Report </a> | -->
<a href="https://huggingface.co/FuseAI"> 🤗 HuggingFace Repo </a> |
<a href="https://github.com/fanqiwan/FuseLLM"> 🐱 GitHub Repo </a> |
</h4>

<p align="center">
    <img src="logo.png" width="60%"> <br>
</p>

</div>

## FuseAI

FuseAI is an open-source research community focused on model fusion topics. 

The community members currently applying model fusion on Foundation and Chat LLMs, with future plans to fuse Agent/MoE LLMs.

Welcome to join us!

## News

<!-- ### FuseChat [SOTA 7B LLM on MT-Bench]

- **Mar 13, 2024:** 🔥🔥🔥 We release a HuggingFace Space for [FuseChat-7B](https://huggingface.co/spaces/FuseAI/FuseChat-7B), try it now!

- **Feb 26, 2024:** 🔥🔥 We release [FuseChat-7B-VaRM](https://huggingface.co/FuseAI/FuseChat-7B-VaRM), which is the fusion of three prominent chat LLMs with diverse architectures and scales, namely [NH2-Mixtral-8x7B](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO), [NH2-Solar-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B), and [OpenChat-3.5-7B](https://huggingface.co/openchat/openchat_3.5). FuseChat-7B-VaRM achieves an average performance of **8.22** on MT-Bench, outperforming various powerful chat LLMs like [Starling-7B](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha), [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat), and [Tulu-2-DPO-70B](https://huggingface.co/allenai/tulu-2-dpo-70b), even surpassing [GPT-3.5 (March)](https://platform.openai.com/docs/models/gpt-3-5-turbo), [Claude-2.1](https://www.anthropic.com/news/claude-2-1), and approaching [Mixtral-8x7B-Instruct](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).

- **Feb 25, 2024:** 🔥 We release [FuseChat-Mixture](https://huggingface.co/datasets/FuseAI/FuseChat-Mixture), which is a comprehensive training dataset covers different styles and capabilities, featuring both human-written and model-generated, and spanning general instruction-following and specific skills.

<p align="center">
    <img src="fig_0.png" width="50%"> <br>
</p>

| Proprietary Models                                                    | #Params | MT-Bench | Open Source Models                                                    | #Params | MT-Bench |
|-----------------------------------------------------------------------|---------|----------|-----------------------------------------------------------------------|---------|----------|
| GPT-4-1106-preview                                                    | -       | 9.32     | Qwen1.5-72B-Chat                                                      | 72B     | 8.61     |
| GPT-4-0613                                                            | -       | 9.18     | Nous-Hermes-2-Mixtral-8x7B-DPO                                        | 8x7B    | 8.33     |
| GPT-4-0314                                                            | -       | 8.96     | Mixtral-8x7B-Instruct-v0.1                                            | 8x7B    | 8.30     |
| Mistral Medium                                                        | -       | 8.61     | 🤗 [FuseChat-7B-VaRM](https://huggingface.co/FuseAI/FuseChat-7B-VaRM) | 7B      | 8.22     |
| GPT-3.5-Turbo-0613                                                    | -       | 8.39     | Starling-LM-7B-alpha                                                  | 7B      | 8.09     |
| GPT-3.5-Turbo-1106                                                    | -       | 8.32     | Tulu-2-DPO-70B                                                        | 70B     | 7.89     |
| 🤗 [FuseChat-7B-VaRM](https://huggingface.co/FuseAI/FuseChat-7B-VaRM) | 7B      | 8.22     | OpenChat-3.5                                                          | 7B      | 7.81     |
| Claude-2.1                                                            | -       | 8.18     | OpenChat-3.5-0106                                                     | 7B      | 7.80     |
| Claude-2.0                                                            | -       | 8.06     | WizardLM-70B-v1.0                                                     | 70B     | 7.71     |
| GPT-3.5-Turbo-0314                                                    | -       | 7.94     | Yi-34B-Chat                                                           | 34B     | 7.67     |
| Claude-1                                                              | -       | 7.90     | Nous-Hermes-2-SOLAR-10.7B                                             | 10.7B   | 7.66     |
 -->
### FuseLLM [Surpassing Llama-2-7B]

- **Jan 22, 2024:** 🔥 We release [FuseLLM-7B](https://huggingface.co/Wanfq/FuseLLM-7B), which is the fusion of three open-source foundation LLMs with distinct architectures, including [Llama-2-7B](https://huggingface.co/meta-llama/Llama-2-7b-hf), [OpenLLaMA-7B](https://huggingface.co/openlm-research/open_llama_7b_v2), and [MPT-7B](https://huggingface.co/mosaicml/mpt-7b).

| Model                                                    | BBH   | ARC-easy | ARC-challenge | BoolQ | HellaSwag | OpenBookQA |
|----------------------------------------------------------|-------|----------|---------------|-------|-----------|------------|
| OpenLLaMA-7B                                             | 33.87 | 69.70    | 41.38         | 72.29 | 74.53     | 41.00      |
| MPT-7B                                                   | 33.38 | 70.12    | 42.15         | 74.74 | 76.25     | 42.40      |
| Llama-2-7B                                               | 39.70 | 74.58    | 46.33         | 77.71 | 76.00     | 44.20      |
| Llama-2-CLM-7B                                           | 40.44 | 74.54    | 46.50         | 76.88 | 76.57     | 44.80      |
| 🤗 [FuseLLM-7B](https://huggingface.co/Wanfq/FuseLLM-7B) | 41.75 | 75.04    | 47.44         | 78.13 | 76.78     | 45.40      |


| Model                                                    | MultiPL-E | TrivialQA | DROP  | LAMBADA | IWSLT2017 | SciBench | 
|----------------------------------------------------------|-----------|-----------|-------|---------|-----------|----------|
| OpenLLaMA-7B                                             | 18.11     | 39.96     | 22.31 | 70.31   | 5.51      | 0.68     |
| MPT-7B                                                   | 17.26     | 28.89     | 23.54 | 70.08   | 5.49      | 0.88     |
| Llama-2-7B                                               | 14.63     | 52.46     | 27.25 | 73.28   | 6.48      | 0.14     |
| Llama-2-CLM-7B                                           | 14.83     | 53.14     | 28.51 | 73.45   | 6.91      | 0.94     |
| 🤗 [FuseLLM-7B](https://huggingface.co/Wanfq/FuseLLM-7B) | 15.56     | 54.49     | 28.97 | 73.72   | 6.75      | 1.65     |


## Citation

Please cite the following paper if you reference our model, code, data, or paper related to FuseLLM.
```
@inproceedings{wan2024knowledge,
  title={Knowledge Fusion of Large Language Models},
  author={Fanqi Wan and Xinting Huang and Deng Cai and Xiaojun Quan and Wei Bi and Shuming Shi},
  booktitle={The Twelfth International Conference on Learning Representations},
  year={2024},
  url={https://openreview.net/pdf?id=jiDsk12qcz}
}
```
<!-- 
Please cite the following paper if you reference our model, code, data, or paper related to FuseChat.
```
@article{wan2024fusechat,
  title={FuseChat: Knowledge Fusion of Chat Models},
  author={Fanqi Wan and Ziyi Yang and Longguang Zhong and Xiaojun Quan and Xinting Huang and Wei Bi},
  journal={arXiv preprint arXiv:2402.16107},
  year={2024}
}
``` -->