Add model card

README.md

@@ -1,14 +1,54 @@
 ---
+license: apache-2.0
 library_name: resyn
+pipeline_tag: text-classification
 tags:
-- model_hub_mixin
+- regex
+- regex-synthesis
+- program-synthesis
 - pytorch
+- model_hub_mixin
 - pytorch_model_hub_mixin
-- regex-synthesis
 - router
+datasets:
+- mrseongminkim/ReSyn
 ---
 
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
-- Code: https://github.com/mrseongminkim/ReSyn
-- Paper: https://arxiv.org/pdf/2603.24624
-- Docs: [More Information Needed]
+# ReSyn — Router
+
+This repository contains the pre-trained **Router** model presented in the paper [ReSyn: A Generalized Recursive Regular Expression Synthesis Framework](https://huggingface.co/papers/2603.24624).
+
+ReSyn is a synthesizer-agnostic divide-and-conquer framework that decomposes complex regular expression synthesis problems into manageable sub-problems by adaptively predicting whether to split examples sequentially (Concatenation) or group them by structural similarity (Union).
+
+**Router** decides *how* to decompose a synthesis problem. Given a set of positive example strings, it classifies the set into one of three actions — **Concat**, **Union**, or **No-Op** — telling the framework whether to split the examples sequentially, group them by structural similarity, or synthesize them directly without further decomposition.
+
+## Links
+
+- **Paper:** [ReSyn: A Generalized Recursive Regular Expression Synthesis Framework](https://huggingface.co/papers/2603.24624)
+- **GitHub Repository:** [mrseongminkim/ReSyn](https://github.com/mrseongminkim/ReSyn)
+- **Dataset:** [mrseongminkim/ReSyn](https://huggingface.co/datasets/mrseongminkim/ReSyn)
+
+## Usage
+
+These are custom PyTorch models that use [`PyTorchModelHubMixin`](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin). The model class is defined in the [GitHub repository](https://github.com/mrseongminkim/ReSyn); clone it first so that the `ReSyn` package is importable, then:
+
+```python
+from ReSyn.model import Router
+
+model = Router.from_pretrained("mrseongminkim/ReSyn-Router").eval()
+```
+
+See [`ReSyn/server.py`](https://github.com/mrseongminkim/ReSyn/blob/main/ReSyn/server.py) for the full input encoding / output decoding used at inference time.
+
+## Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@inproceedings{kim2026resyn,
+  title={ReSyn: A Generalized Recursive Regular Expression Synthesis Framework},
+  author={Kim, Seongmin and Cheon, Hyunjoon and Kim, Su-Hyeon and Han, Yo-Sub and Ko, Sang-Ki},
+  booktitle={Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-26)},
+  year={2026}
+}
+```