File size: 2,127 Bytes
e4f86d5
 
 
 
 
 
 
 
 
 
 
 
 
58866a2
e4f86d5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5071653
e4f86d5
 
 
 
5071653
 
 
 
 
 
 
e41e1f2
 
 
5071653
 
 
 
 
 
e4f86d5
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
---
license: mit
---

<p align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/bp_DZR79-mTj8Z6GJe9B0.png" width="80%" />
</p>

<font size=3><div align='center' >  
[[๐Ÿ“– arXiv Paper](https://arxiv.org/abs/2406.08487)] 
[[๐Ÿ“Š MM-RLHF Data](https://huggingface.co/datasets/yifanzhang114/MM-RLHF)] 
[[๐Ÿ“ Homepage](https://mm-rlhf.github.io/)] 
[[๐Ÿ† Reward Model](https://huggingface.co/yifanzhang114/MM-RLHF-Reward-7B-llava-ov-qwen)] 

[[๐Ÿ”ฎ MM-RewardBench](https://huggingface.co/datasets/yifanzhang114/MM-RLHF-RewardBench)] 
[[๐Ÿ”ฎ MM-SafetyBench](https://github.com/yfzhang114/mmrlhf-eval)] 
[[๐Ÿ“ˆ Evaluation Suite](https://github.com/yfzhang114/mmrlhf-eval)] 
</div></font>


# The Next Step Forward in Multimodal LLM Alignment

**[2025/02/10]** ๐Ÿ”ฅ We are proud to open-source **MM-RLHF**, a comprehensive project for aligning Multimodal Large Language Models (MLLMs) with human preferences. This release includes:

- A **high-quality MLLM alignment dataset**.
- A **strong Critique-Based MLLM reward model** and its training algorithm.
- A **novel alignment algorithm MM-DPO**.
- **Two new benchmarks**.

Our dataset and algorithms enable consistent performance improvements across **10 dimensions** and **27 benchmarks**.
<p align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/8nVZQd8bfB6NJIixCv6_X.png" width="80%" />
</p>


## Use

### Intended use

The model was trained on [MM-RLHF data](https://huggingface.co/datasets/yifanzhang114/MM-RLHF) and have the ability to interact with images, multi-image and videos. 


![image/png](https://cdn-uploads.huggingface.co/production/uploads/623d8ca4c29adf5ef6175615/2RQJMhntIwE15y9lEtBfP.png)

**Feel free to share your generations in the Community tab!**

### Generation

We provide the simple generation process for using our model. For more details, you could refer to [Github](https://github.com/yfzhang114/MM-RLHF).

## Citation

If you find it useful for your research and applications, please cite related papers/blogs using this BibTeX:
```bibtex

```