Add library_name and pipeline_tag to metadata

This PR adds the `library_name` and `pipeline_tag` to the model card metadata. The `library_name` is set to `transformers` given the model's compatibility with the Hugging Face Transformers library. The `pipeline_tag` is set to `text-generation` as the model is used for text generation tasks.

README.md

@@ -1,11 +1,13 @@
 ---
 base_model:
 - Qwen/Qwen2.5-7B-Instruct
-license: apache-2.0
-language:
-- en
 datasets:
 - chtmp223/CLIPPER
+language:
+- en
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
 ---
 
 # Qwen2.5-7B-CLIPPER
@@ -43,26 +45,4 @@ Please check [our paper](https://arxiv.org/abs/2502.14854) for more details on t
 | learning_rate                    | 1.0e-6       |
 | lr_scheduler_type                | cosine       |
 | max_length                       | 131072       |
-| num_train_epochs                 | 1            |
-| optim                            | adamw_torch  |
-
-#### Software
-
-Training code is adapted from [https://github.com/Qihoo360/360-LLaMA-Factory/tree/1b5398f539c7d94a530f3f32b53553a3b1928314](https://github.com/Qihoo360/360-LLaMA-Factory/tree/1b5398f539c7d94a530f3f32b53553a3b1928314).
-
-## 🤗 Inference
-Inference is done with [vLLM](https://github.com/vllm-project/vllm) on 1 A100-80GB.  
-
-## 📜 Citation 
-
-```
-@misc{pham2025clippercompressionenableslongcontext,
-      title={CLIPPER: Compression enables long-context synthetic data generation}, 
-      author={Chau Minh Pham and Yapei Chang and Mohit Iyyer},
-      year={2025},
-      eprint={2502.14854},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2502.14854}, 
-}
-```
+| num_train_epochs                 | 1            |\n| optim                            | adamw_torch  |\n\n#### Software\n\nTraining code is adapted from [https://github.com/Qihoo360/360-LLaMA-Factory/tree/1b5398f539c7d94a530f3f32b53553a3b1928314](https://github.com/Qihoo360/360-LLaMA-Factory/tree/1b5398f539c7d94a530f3f32b53553a3b1928314).\n\n## 🤗 Inference\nInference is done with [vLLM](https://github.com/vllm-project/vllm) on 1 A100-80GB.  \n\n## 📜 Citation \n\n```\n@misc{pham2025clippercompressionenableslongcontext,\n      title={CLIPPER: Compression enables long-context synthetic data generation}, \n      author={Chau Minh Pham and Yapei Chang and Mohit Iyyer},\n      year={2025},\n      eprint={2502.14854},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      url={https://arxiv.org/abs/2502.14854}, \n}\n```