Add library_name and pipeline_tag to metadata

This PR adds `library_name` and `pipeline_tag` to the model card metadata.
The `library_name` is set to `transformers` as the models are compatible with the Hugging Face Transformers library. The `pipeline_tag` is set to `text-generation` as these are language models.

README.md

@@ -1,6 +1,11 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- code-generation
 ---
+
 **Paper**: [https://arxiv.org/pdf/2502.07780](https://arxiv.org/pdf/2502.07780)  
 **Code**: https://github.com/IST-DASLab/DarwinLM  
 **Models**: [DarwinLM-2.7B](https://huggingface.co/Shengkun/DarwinLM-2.7B), [DarwinLM-4.6B](https://huggingface.co/Shengkun/DarwinLM-4.6B), [DarwinLM-8.4B](https://huggingface.co/Shengkun/DarwinLM-8.4B)  
@@ -9,14 +14,13 @@ license: apache-2.0
 ---
 
 This repository contains the weights of DarwinLM, an evolutionary structured pruning methods for large language models, as introduced in our paper. DarwinLM builds upon an evolutionary search process, generating multiple offspring models in each generation through mutation, and selecting the fittest for survival.
-```
+```python
 # Please add trust_remote_code=True as the repo includes custom code to load and run DarwinLM
 model = AutoModelForCausalLM.from_pretrained("Shengkun/DarwinLM-2.7B", trust_remote_code=True)
 ```
 
 ## Downstream Tasks
 
-
 **2.7B**
 
 | Method                     | Param. | SciQ | PIQA | WG   | ArcE | ArcC | HS   | LogiQA | BoolQ | Avg  |
@@ -52,8 +56,6 @@ model = AutoModelForCausalLM.from_pretrained("Shengkun/DarwinLM-2.7B", trust_rem
 |                           | **OLMO-0424 (2.05T)**   | 7B     | 96.1 | 80.1 | 72.1 | 73.8 | 49.2 | 78.0 | 29.3   | 80.8  | 52.1 | 67.9 |
 |                           | *DarwinLM (10.0B)*      | 8.4B   | 89.5 | 78.1 | 70.7 | 79.6 | 57.6 | 74.9 | 33.5   | 73.9  | 57.9 | 68.4 |
 
-
-
 ## Bibtex
 ```
 @article{tang2025darwinlm,