Improve model card: Add Transformers library tag, paper link, GitHub link, and usage details

This PR enhances the model card for the MahaParaphrase-BERT model by:

- Adding `library_name: transformers` to the metadata, which enables proper integration and displays an auto-generated usage snippet on the model page, as the model's configuration indicates compatibility with the `transformers` library.
- Updating the paper link to the official publication: [MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models](https://huggingface.co/papers/2508.17444).
- Adding an explicit link to the [L3Cube-MahaNLP GitHub repository](https://github.com/l3cube-pune/MarathiNLP) for code and resources.
- Including a "Usage" section that directs users to the GitHub repository and an associated Colab notebook for practical examples.
- Updating the citation section to refer to the specific paper for this model.

Please review and merge this PR if these improvements are acceptable.

README.md

@@ -1,30 +1,38 @@
 ---
-license: cc-by-4.0
 datasets:
 - l3cube-pune/MahaParaphrase
 language:
 - mr
+license: cc-by-4.0
 metrics:
 - accuracy
 pipeline_tag: text-classification
+library_name: transformers
 ---
+
 # MahaParaphrase-BERT Model
 
 **MahaParaphrase-BERT** is a **MahaBERT** model ([l3cube-pune/marathi-bert-v2](https://huggingface.co/l3cube-pune/marathi-bert-v2)) fine-tuned on the **L3Cube-MahaParaphrase Dataset**, a high-quality Marathi paraphrase detection corpus. The dataset consists of 8,000 sentence pairs annotated as Paraphrase (P) or Non-paraphrase (NP).
 
 This model is trained specifically for Marathi Paraphrase Detection task.
 
-For more details on the **L3Cube-MahaParaphrase Dataset**, visit the [dataset link](https://github.com/l3cube-pune/MarathiNLP).
+More details on the model, training methodology, and evaluation results can be found in the paper: [MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models](https://huggingface.co/papers/2508.17444).
+
+For further resources, including the **L3Cube-MahaParaphrase Dataset** and code, visit the [L3Cube-MahaNLP GitHub repository](https://github.com/l3cube-pune/MarathiNLP).
+
+## Usage
+
+This model can be used with the Hugging Face `transformers` library. For detailed usage examples and more information on the `mahaNLP` library and its integration, please refer to the [L3Cube-MahaNLP GitHub repository](https://github.com/l3cube-pune/MarathiNLP) and its associated [Colab notebook](https://colab.research.google.com/drive/1POx3Bi1cML6-s3Z3u8g8VpqzpoYCyv2q).
 
-More details on the model, training methodology, and evaluation results can be found in our [paper](coming soon).
+## Citing
 
-## Citing:
-If you use this model, please cite it as follows:
-```
-@article{joshi2022l3cube,
-  title={L3cube-mahanlp: Marathi natural language processing datasets, models, and library},
-  author={Joshi, Raviraj},
-  journal={arXiv preprint arXiv:2205.14728},
-  year={2022}
+If you use this model or the associated dataset, please cite the following paper:
+```bibtex
+@article{mahaparaphrase2025,
+  title={MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models},
+  author={Please refer to the paper for authors},
+  journal={arXiv preprint arXiv:2508.17444},
+  year={2025},
+  url={https://arxiv.org/abs/2508.17444}
 }
 ```