| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: text-classification | |
| # ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models | |
| [](https://arxiv.org/abs/2407.04693) | |
| [](./LICENSE) | |
| This page holds the ANAH-v2 model which is trained based on the InternLM2-7B. It is fine-tuned to annotate the hallucination in LLMs' responses. | |
| More information please refer to our [project page](https://github.com/open-compass/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/example/anahv2_prompt.py). | |
| We also provide some [examples](https://github.com/open-compass/ANAH/blob/main/example) of using the ANAH-v2 annotator, which you can refer to for annotating your content. | |
| ## 🖊️ 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} | |
| } | |
| ``` |