Update README.md

README.md

@@ -1,3 +1,10 @@
+---
+tags:
+- protein language model
+datasets:
+- IEDB
+---
+
 # TransHLA2.0-BIND
 
 A minimal Hugging Face-compatible PyTorch model for peptide–HLA binding classification using ESM with optional LoRA and cross-attention. There is no custom predict API; inference follows the training path: tokenize peptide and HLA pseudosequence with the ESM tokenizer, pad or truncate to fixed lengths (default peptide=16, HLA=36), run a forward pass as `logits, features = model(epitope_ids, hla_ids)`, then apply softmax to get the binding probability.
@@ -14,6 +21,12 @@ Requirements:
 ```bash
 pip install torch transformers peft
 ```
+## Usage (Transformers)
+```python
+model_id = "SkywalkerLu/TransHLA2.0"
+model = AutoModel.from_pretrained(model_id, trust_remote_code=True).to(device).eval()
+```
+```
 ## How to use TransHLA2.0-BIND
 ```python
 import torch