metadata
license: apache-2.0
library_name: transformers
pipeline_tag: text-classification
tags:
- hallucination-detection
- text-classification
language:
- en
ANAH: Analytical Annotation of Hallucinations in Large Language Models
This page holds the InternLM2-7B model which is trained with the ANAH dataset. It is fine-tuned to annotate the hallucination in LLM's responses.
More information please refer to our project page.
🤗 How to use the model
You have to follow the prompt in our paper to annotate the hallucination.
The models follow the conversation format of InternLM2-chat, with the template protocol as:
dict(role='user', begin='<|im_start|>user
', end='<|im_end|>
'),
dict(role='assistant', begin='<|im_start|>assistant
', end='<|im_end|>
'),
🖊️ Citation
If you find this project useful in your research, please consider citing:
@article{ji2024anah,
title={ANAH: Analytical Annotation of Hallucinations in Large Language Models},
author={Ji, Ziwei and Gu, Yuzhe and Zhang, Wenwei and Lyu, Chengqi and Lin, Dahua and Chen, Kai},
journal={arXiv preprint arXiv:2405.20315},
year={2024}
}
Code: The source code for training and evaluating this model can be found at https://github.com/open-compass/ANAH