初始化项目，由ModelHub XC社区提供模型

Model: bmbgsj/ProRAG
Source: Original Platform

README.md

@@ -0,0 +1,49 @@
+---
+language:
+- en
+- zh
+license: apache-2.0
+library_name: transformers
+tags:
+- qwen3
+- text-generation
+- casual-lm
+base_model: Qwen/Qwen3-8B
+pipeline_tag: text-generation
+arxiv: 2601.21912
+---
+
+# Model Card for ProRAG
+
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) based on the methodology described in the paper associated with arXiv ID: **2601.21912**.
+
+## Model Details
+
+- **Base Model:** Qwen3-8B
+- **Language:** English, Chinese (and others supported by Qwen3)
+- **Paper:** [View on arXiv](https://arxiv.org/abs/2601.21912)
+- **Library:** Transformers
+
+## 💻 Code & Inference
+
+For inference code, usage examples, and reproduction scripts, please refer to our GitHub repository:
+
+👉 **[Click here to view the GitHub Repository](https://github.com/lilinwz/ProRAG/tree/main)**
+
+*(Please verify the details and instructions on the GitHub page.)*
+
+## Citation
+
+If you use this model or the associated paper in your research, please cite:
+
+```bibtex
+@misc{wang2026proragprocesssupervisedreinforcementlearning,
+      title={ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation}, 
+      author={Zhao Wang and Ziliang Zhao and Zhicheng Dou},
+      year={2026},
+      eprint={2601.21912},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI},
+      url={https://arxiv.org/abs/2601.21912}, 
+}
+```