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README.md
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# LLaMA3-iterative-DPO-final
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## Introduction
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We release an unofficial checkpoint of a state-of-the-art instruct model of its class, **LLaMA3-iterative-DPO-final**.
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On all three widely-used instruct model benchmarks: **Alpaca-Eval-V2**, **MT-Bench**, **Chat-Arena-Hard**, our model outperforms all models of similar size (e.g., LLaMA-3-8B-it), most large open-sourced models (e.g., Mixtral-8x7B-it),
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# LLaMA3-iterative-DPO-final
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* **Paper**: [RLHF Workflow: From Reward Modeling to Online RLHF](https://arxiv.org/pdf/2405.07863) (Published in TMLR, 2024)
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* **Authors**: Hanze Dong*, Wei Xiong*, Bo Pang*, Haoxiang Wang*, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
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* **Code**: https://github.com/RLHFlow/Online-RLHF
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## Introduction
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We release an unofficial checkpoint of a state-of-the-art instruct model of its class, **LLaMA3-iterative-DPO-final**.
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On all three widely-used instruct model benchmarks: **Alpaca-Eval-V2**, **MT-Bench**, **Chat-Arena-Hard**, our model outperforms all models of similar size (e.g., LLaMA-3-8B-it), most large open-sourced models (e.g., Mixtral-8x7B-it),
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