You can deploy this model and start earning money today!

opencompass/
anah-7b

Name: anah-7b
Rating: 2.5 (14 reviews)

hallucination-detection

Views

No views yet

ANAH: Analytical Annotation of Hallucinations in Large Language Models

arXiv

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:

python

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

opencompass/anah-7b

ANAH: Analytical Annotation of Hallucinations in Large Language Models

🤗 How to use the model

🖊️ Citation

opencompass/
anah-7b