Add `library_name` and `pipeline_tag` to model card

This PR improves the discoverability and usability of the ProLLaMA model by adding the `library_name: transformers` and `pipeline_tag: text-generation` to the model card's metadata.

- The `library_name` tag ensures that the model is correctly recognized as a Transformers-compatible model, enabling an automated code snippet on the Hub page for easy usage.
- The `pipeline_tag` helps users find this model when searching for text generation models, specifically in the context of protein language processing.

The existing content of the model card remains unchanged to reflect the majority consensus among colleagues.

README.md

@@ -1,6 +1,9 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
 ---
+
 # ProLLaMA: A Protein Large Language Model for Multi-Task Protein Language Processing
 
 [Paper on arxiv](https://arxiv.org/abs/2402.16445) for more information
@@ -106,7 +109,8 @@ if __name__ == '__main__':
                 s = generation_output[0]
                 output = tokenizer.decode(s,skip_special_tokens=True)
                 print("Output:",output)
-                print("\n")
+                print("
+")
         else:
             outputs=[]
             with open(args.input_file, 'r') as f:
@@ -126,7 +130,8 @@ if __name__ == '__main__':
                 output = tokenizer.decode(s,skip_special_tokens=True)
                 outputs.append(output)
             with open(args.output_file,'w') as f:
-                f.write("\n".join(outputs))
+                f.write("
+".join(outputs))
             print("All the outputs have been saved in",args.output_file)
 ```