Create README.md

README.md

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+---
+library_name: transformers
+license: mit
+datasets:
+- CodeGoat24/UniGenBench-Eval-Images
+base_model:
+- CodeGoat24/UnifiedReward-2.0-qwen3vl-32b
+---
+
+
+# UniGenBench-EvalModel-qwen-72b-v1
+
+This model is tailored for offline T2I model evaluation on [UniGenBench](https://github.com/CodeGoat24/UniGenBench).
+
+Feel free to use this model to assess and compare the performance of your models.
+
+For further details, please refer to the following resources:
+- 📰 Paper: https://arxiv.org/pdf/2508.20751
+- 🪐 Project Page: https://codegoat24.github.io/UnifiedReward/Pref-GRPO
+- 🤗 UniGenBench: https://github.com/CodeGoat24/UniGenBench
+- 🤗 Leaderboard: https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard
+- 👋 Point of Contact: [Yibin Wang](https://codegoat24.github.io)
+
+
+## Citation
+
+```bibtex
+@article{UniGenBench++,
+  title={UniGenBench++: A Unified Semantic Evaluation Benchmark for Text-to-Image Generation},
+  author={Wang, Yibin and Li, Zhimin and Zang, Yuhang and Bu, Jiazi and Zhou, Yujie and Xin, Yi and He, Junjun and Wang, Chunyu and Lu, Qinglin and Jin, Cheng and others},
+  journal={arXiv preprint arXiv:2510.18701},
+  year={2025}
+}
+
+@article{UniGenBench,
+  title={Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning},
+  author={Wang, Yibin and Li, Zhimin and Zang, Yuhang and Zhou, Yujie and Bu, Jiazi and Wang, Chunyu and Lu, Qinglin, and Jin, Cheng and Wang, Jiaqi},
+  journal={arXiv preprint arXiv:2508.20751},
+  year={2025}
+}
+```