Add model card and metadata

README.md

@@ -1,4 +1,34 @@
-This tool is developed as part of our work  
-[*How to Fine-Tune a Reasoning Model? A Teacher–Student Cooperation Framework to Synthesize Student-Consistent SFT Data*](https://github.com/CoopReason/TESSY/blob/main/paper/TESSY.pdf).  
+---
+library_name: transformers
+pipeline_tag: text-classification
+---
 
-For more details, please refer to the [GitHub repository](https://github.com/CoopReason/TESSY/).
+# TESSY: Boundary Predictor
+
+This model is a boundary predictor developed as part of the **TESSY** (Teacher–Student Cooperation Data Synthesis) framework, as presented in the paper:
+[*How to Fine-Tune a Reasoning Model? A Teacher–Student Cooperation Framework to Synthesize Student-Consistent SFT Data*](https://huggingface.co/papers/2604.14164).
+
+## Model Description
+
+TESSY is a framework designed to bridge the stylistic gap between teacher-generated synthetic data and the student model's distribution. It interleaves teacher and student models to alternately generate style and non-style tokens.
+
+The **Boundary Predictor** is a critical component of this system; it identifies the transitions between reasoning steps (capability tokens) and non-reasoning stylistic content (style tokens) within a given problem. This allows the framework to determine when to switch between the teacher model (for reasoning) and the student model (for style).
+
+## Links
+
+- **Paper:** [arXiv:2604.14164](https://huggingface.co/papers/2604.14164)
+- **Code:** [GitHub - CoopReason/TESSY](https://github.com/CoopReason/TESSY)
+- **Dataset:** [TESSY-Code-80K](https://huggingface.co/datasets/CoopReason/TESSY-Code-80K)
+
+## Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@article{TESSY,
+  title={How to Fine-Tune a Reasoning Model? A Teacher--Student Cooperation Framework to Synthesize Student-Consistent SFT Data},
+  author={Huang, Zixian and Yang, Kaichen and Huang, Xu and Hao, Feiyang and Ge, Qiming and Li, Bowen and Du, He and Chen, Kai and Guo, Qipeng},
+  journal={arXiv preprint arXiv:2604.14164},
+  year={2026}
+}
+```