Add model card for SEPO

This PR adds a comprehensive model card for the SEPO model, linking it to the paper [Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods](https://huggingface.co/papers/2502.01384).

It includes the `pipeline_tag: text-generation` to make the model discoverable. A link to the official GitHub repository and a sample usage snippet for downloading the model checkpoint from the Hub are also provided.

Please review and merge this PR if everything looks good.

README.md

@@ -0,0 +1,51 @@
+---
+pipeline_tag: text-generation
+---
+
+# Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods
+
+This repository contains the code for the `SEPO` algorithm presented in the paper: [Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods](https://huggingface.co/papers/2502.01384).
+
+`SEPO` (Score Entropy Policy Optimization) is an efficient, broadly applicable, and theoretically justified policy gradient algorithm for fine-tuning discrete diffusion models over non-differentiable rewards. Our numerical experiments across several discrete generative tasks demonstrate the scalability and efficiency of our method, including applications on fine-tuning a masked diffusion language model on DNA sequences.
+
+<p align="center">
+<img src="https://github.com/ozekri/SEPO/blob/main/img/denoising_RLHF.gif" width=80% height=80% alt="Denoising RLHF process visualization">
+</p>
+
+For more details and the full implementation, please refer to the [official GitHub repository](https://github.com/ozekri/SEPO).
+
+## Sample Usage: Download Checkpoint
+
+You can download the fine-tuned models from Hugging Face directly using the `huggingface_hub` Python library to reproduce results:
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Example: Download the SEPO fine-tuned model checkpoint
+ckpt_path = hf_hub_download(
+    repo_id="Xssama/SEPO_DNA",
+    filename="finetuned_sepo_kl.ckpt",  # finetuned_sepo_kl_gf.ckpt for SEPO with gradient flow
+    cache_dir="./checkpoints"  # Optional: specify your preferred local directory
+)
+
+print(f"Checkpoint downloaded to: {ckpt_path}")
+```
+
+Alternatively, you can use `wget`:
+
+```bash
+wget https://huggingface.co/Xssama/SEPO-DNA/resolve/main/finetuned_sepo_kl.ckpt -P ./checkpoints/
+```
+
+## Citation
+
+If you find this work useful in your research, please consider citing:
+
+```bibtex
+@article{zekri2025fine,
+  title={Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods},
+  author={Zekri, Oussama and Boull{\'e}, Nicolas},
+  journal={arXiv preprint arXiv:2502.01384},
+  year={2025}
+}
+```