Add model card and metadata for dUltra

Hi! I'm Niels from the Hugging Face community science team.

This PR adds a model card for dUltra, an on-policy reinforcement learning framework for masked diffusion language models.

The PR includes:
- Relevant metadata (pipeline tag and library name).
- Links to the paper and the official GitHub repository.
- A summary of the model's architecture and training approach.
- A sample usage code snippet based on the official README.
- BibTeX citation information.

Please feel free to merge if this looks good to you!

README.md

@@ -0,0 +1,50 @@
+---
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- diffusion
+- reinforcement-learning
+- grpo
+---
+
+# dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning
+
+dUltra is an on-policy reinforcement learning framework based on Group Relative Policy Optimization (GRPO) that learns unmasking strategies for efficient parallel decoding in masked diffusion language models (MDLMs). 
+
+By training an unmasking planner head that predicts per-token unmasking likelihoods, dUltra enables better exploitation of parallel generation. Across mathematical reasoning and code generation tasks, it achieves superior accuracy-efficiency trade-offs compared to state-of-the-art heuristic and distillation baselines.
+
+- **Paper:** [dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning](https://huggingface.co/papers/2512.21446)
+- **Repository:** [https://github.com/chinsengi/dUltra-os](https://github.com/chinsengi/dUltra-os)
+
+## Sample Usage
+
+To use this model, you can load it using the following code snippet from the official repository (requires `trust_remote_code=True`):
+
+```python
+import torch
+from model.llada.lladou import LLaDOUModelLM
+from transformers import AutoTokenizer
+
+model = LLaDOUModelLM.from_pretrained(
+            "sengi/dUltra-math",
+            trust_remote_code=True,
+            torch_dtype=torch.bfloat16,
+        )
+tokenizer = AutoTokenizer.from_pretrained("sengi/dUltra-math")
+```
+
+## Citation
+
+If you find this work useful, please cite:
+
+```bibtex
+@misc{chen2025dultraultrafastdiffusionlanguage,
+      title={dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning},
+      author={Shirui Chen and Jiantao Jiao and Lillian J. Ratliff and Banghua Zhu},
+      year={2025},
+      eprint={2512.21446},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2512.21446},
+}
+```