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README.md
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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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and strong proprietary models (e.g., GPT-3.5-turbo-0613). The model is trained with open-sourced datasets without any additional human-/GPT4-labeling.
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## Model Releases
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See the [collection](https://huggingface.co/collections/RLHFlow/online-rlhf-663ae95fade1a39663dab218) of the training set, reward/preference model, SFT model.
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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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and strong proprietary models (e.g., GPT-3.5-turbo-0613). The model is trained with open-sourced datasets without any additional human-/GPT4-labeling.
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Even better, we provide a [detailed recipe](https://github.com/RLHFlow/Online-RLHF) to reproduce the model. Enjoy!
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## Model Releases
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See the [collection](https://huggingface.co/collections/RLHFlow/online-rlhf-663ae95fade1a39663dab218) of the training set, reward/preference model, SFT model.
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