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license: apache-2.0 |
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--- |
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# ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models |
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[![arXiv](https://img.shields.io/badge/arXiv-2407.04693-b31b1b.svg)](https://arxiv.org/abs/2407.04693) |
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[![license](https://img.shields.io/github/license/InternLM/opencompass.svg)](./LICENSE) |
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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. |
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More information please refer to our [project page](https://open-compass.github.io/ANAH/). |
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## ๐ค How to use the model |
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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). |
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The models follow the conversation format of InternLM2-chat, with the template protocol as: |
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```python |
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dict(role='user', begin='<|im_start|>user\n', end='<|im_end|>\n'), |
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dict(role='assistant', begin='<|im_start|>assistant\n', end='<|im_end|>\n'), |
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``` |
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## ๐๏ธ Citation |
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If you find this project useful in your research, please consider citing: |
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``` |
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@article{gu2024anah, |
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title={ANAH-v2: Scaling Analytical Hallucination Annotation of Large Language Models}, |
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author={Gu, Yuzhe and Ji, Ziwei and Zhang, Wenwei and Lyu, Chengqi and Lin, Dahua and Chen, Kai}, |
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journal={arXiv preprint arXiv:2407.04693}, |
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year={2024} |
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} |
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``` |