Self-Rewarding Language Model (wip)

Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI

They really took the title of the DPO paper to heart.

May generalize the framework so one can add SPIN as well.

Appreciation

A16Z Open Source AI Grant Program and 🤗 Huggingface for the generous sponsorships, as well as my other sponsors, for affording me the independence to open source current artificial intelligence research

Citation

@misc{yuan2024selfrewarding,
    title   = {Self-Rewarding Language Models}, 
    author  = {Weizhe Yuan and Richard Yuanzhe Pang and Kyunghyun Cho and Sainbayar Sukhbaatar and Jing Xu and Jason Weston},
    year    = {2024},
    eprint  = {2401.10020},
    archivePrefix = {arXiv},
    primaryClass = {cs.CL}
}

@article{Chen2024SelfPlayFC,
    title   = {Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models},
    author  = {Zixiang Chen and Yihe Deng and Huizhuo Yuan and Kaixuan Ji and Quanquan Gu},
    journal = {ArXiv},
    year    = {2024},
    volume  = {abs/2401.01335},
    url     = {https://api.semanticscholar.org/CorpusID:266725672}
}

@article{Rafailov2023DirectPO,
    title   = {Direct Preference Optimization: Your Language Model is Secretly a Reward Model},
    author  = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Stefano Ermon and Christopher D. Manning and Chelsea Finn},
    journal = {ArXiv},
    year    = {2023},
    volume  = {abs/2305.18290},
    url     = {https://api.semanticscholar.org/CorpusID:258959321}
}

License

lucidrains/self-rewarding-lm-pytorch

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