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--- |
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library_name: diffusers |
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license: mit |
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pipeline_tag: text-to-image |
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base_model: |
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- black-forest-labs/FLUX.1-dev |
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--- |
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# Model Summary |
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This model is GRPO trained using [UnifiedReward-Flex](https://huggingface.co/collections/CodeGoat24/unifiedreward-flex) as reward on the training dataset of [UniGenBench](https://github.com/CodeGoat24/UniGenBench). |
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π The inference code is available at [Github](https://github.com/CodeGoat24/Pref-GRPO/blob/main/inference/flux_dist_infer.sh). |
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For further details, please refer to the following resources: |
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- π° Paper: https://arxiv.org/abs/2602.02380 |
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- πͺ Project Page: https://codegoat24.github.io/UnifiedReward/flex |
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- π€ Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-flex |
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- π€ Dataset: https://huggingface.co/datasets/CodeGoat24/UnifiedReward-Flex-SFT-90K |
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- π Point of Contact: [Yibin Wang](https://codegoat24.github.io) |
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# Qualitative Results |
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# Quantitative Results |
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## Citation |
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```bibtex |
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@article{unifiedreward-flex, |
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title={Unified Personalized Reward Model for Vision Generation}, |
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author={Wang, Yibin and Zang, Yuhang and Han, Feng and Bu, Jiazi and Zhou, Yujie and Jin, Cheng and Wang, Jiaqi}, |
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journal={arXiv preprint arXiv:2602.02380}, |
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year={2026} |
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} |
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``` |