Improve model card: add metadata, paper/code links and citation

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

This PR improves the model card for **daVinci-origin-7B** by adding:
- Metadata for `pipeline_tag: text-generation` and `library_name: transformers`.
- Links to the research paper and the official GitHub repository.
- A citation section using the BibTeX provided in the project's repository.

These changes help users find the model through the Hub's filtering tools and provide better context for the research.

README.md

@@ -1,10 +1,33 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- science
+- data-darwinism
 ---
 
 # daVinci-origin-7B
 
-**daVinci-origin-7B** is a fully transparent, 7-billion parameter foundation model trained from scratch. It serves as a "clean-room" baseline for the research paper [*Data Darwinism -- Part1: Unlocking the Value of Scientific Data for Pre-training*](https://arxiv.org/pdf/2602.07824).
+**daVinci-origin-7B** is a fully transparent, 7-billion parameter foundation model trained from scratch. It serves as a "clean-room" baseline for the research paper [*Data Darwinism -- Part1: Unlocking the Value of Scientific Data for Pre-training*](https://huggingface.co/papers/2602.07824).
 
 Unlike most open-source models, daVinci-origin-7B was explicitly trained on a dataset **strictly excluding scientific content** (books and research papers). This unique design allows researchers to unambiguously attribute performance gains to specific domain data injection strategies during continued pre-training.
 
+## Resources
+
+- **Paper:** [Data Darwinism Part I: Unlocking the Value of Scientific Data for Pre-training](https://huggingface.co/papers/2602.07824)
+- **GitHub Repository:** [GAIR-NLP/Data-Darwinism](https://github.com/GAIR-NLP/Data-Darwinism)
+- **Dataset (Darwin-Science):** [GAIR/Darwin-Science](https://huggingface.co/datasets/GAIR/Darwin-Science)
+
+## Citation
+
+If you use this model or the associated research in your work, please cite:
+
+```bibtex
+@article{qin2026data,
+  title={Data Darwinism Part I: Unlocking the Value of Scientific Data for Pre-training},
+  author={Qin, Yiwei and Huang, Zhen and Mi, Tiantian and Si, Weiye and Zhou, Chenyang and Guo, Qipeng and Feng, Siyuan and Liu, Pengfei},
+  journal={arXiv preprint arXiv:2602.07824},
+  year={2026}
+}
+```