--- license: apache-2.0 library_name: transformers pipeline_tag: text-classification --- # 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 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} } ```