Add metadata, link to paper and code

README.md

@@ -1,5 +1,13 @@
+---
+license: mit
+library_name: transformers
+pipeline_tag: feature-extraction
+---
+
 # PDeepPP: A Comprehensive Protein Language Model Hub
 
+This repository contains the model as presented in [PDeepPP:A Deep learning framework with Pretrained Protein language for peptide classification](https://huggingface.co/papers/2502.15610).
+
 PDeepPP is a hybrid protein language model designed to predict post-translational modification (PTM) sites, analyze biologically relevant features, and support a wide range of protein sequence analysis tasks. This repository serves as the central hub for accessing and exploring various specialized PDeepPP models, each fine-tuned for specific tasks, such as PTM site prediction, bioactivity analysis, and more.
 
 The models in this repository can all be used on their corresponding datasets on GitHub ([https://github.com/fondress/PDeepPP/tree/main])
@@ -87,7 +95,7 @@ To use any of the models, you need to install the required dependencies, such as
 pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
 pip install transformers
 ```
-Here’s a quick example of how to load a model(The use of models with specific biological features can be found in Task-Specific Models.):
+Here’s a quick example of how to load a model (The use of models with specific biological features can be found in Task-Specific Models.):
 
 ```python
 from transformers import AutoModel, AutoTokenizer
@@ -109,13 +117,16 @@ Refer to the `PDeepPPConfig` class in the source repository for details on avail
 
 ---
  ## Citation
- If you use any of the PDeepPP models in your research, please cite the associated paper or repository:
+
+ If you use any of the PDeepPP models in your research, please cite the associated paper:
 
 ```
- @article{your_reference,
+@article{your_reference,
   title={A general language model for peptide identification},
   author={Author Name},
   journal={Journal Name},
   year={2025}
 }
-```
+```
+
+Code: [https://github.com/fondress/PDeepPP](https://github.com/fondress/PDeepPP)