---
license: apache-2.0
---

# ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models

[![arXiv](https://img.shields.io/badge/arXiv-2407.04693-b31b1b.svg)](https://arxiv.org/abs/2407.04693)
[![license](https://img.shields.io/github/license/InternLM/opencompass.svg)](./LICENSE)

This page holds the ANAH-v2 model which is trained base on the Internlm2-7B. It is fine-tuned to annotate the hallucination in LLM's responses.

More information please refer to our [project page](https://open-compass.github.io/ANAH/).

## 🤗 How to use the model

You have to follow the prompt in [our paper](https://arxiv.org/abs/2407.04693) to annotate the hallucination and you can find it easily [here](https://github.com/open-compass/ANAH/blob/main/prompt_v2.py).

The models follow the conversation format of InternLM2-chat, with the template protocol as:

```python
dict(role='user', begin='<|im_start|>user\n', end='<|im_end|>\n'),
dict(role='assistant', begin='<|im_start|>assistant\n', end='<|im_end|>\n'),
```

## 🖊️ Citation

If you find this project useful in your research, please consider citing:

```
@article{gu2024anah,
  title={ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models},
  author={Gu, Yuzhe and Ji, Ziwei and Zhang, Wenwei and Lyu, Chengqi and Lin, Dahua and Chen, Kai},
  journal={arXiv preprint arXiv:2407.04693},
  year={2024}
}
```