Add model specs, GitHub link, and update citation

README.md

@@ -27,6 +27,19 @@ HELM-BERT is a BERT-style encoder designed specifically for peptide sequences in
 - **Span Masking**: Contiguous token masking for improved contextual learning
 - **nGiE**: n-gram Induced Encoding layer for local pattern recognition
 
+Please check the [official repository](https://github.com/clinfo/HELM-BERT) for more implementation details and updates.
+
+## Model Specifications
+
+| Parameter | Value |
+|-----------|-------|
+| Parameters | 54.8M |
+| Hidden size | 768 |
+| Layers | 6 |
+| Attention heads | 12 |
+| Vocab size | 78 |
+| Max token length | 512 |
+
 ## How to Use
 
 ```python
@@ -61,4 +74,4 @@ Pretrained on deduplicated peptide sequences from:
 
 ## License
 
-MIT License
+MIT License