Update README.md

README.md

@@ -33,10 +33,11 @@ This model was further fine-tuned on a custom drug–drug interaction dataset to
 ```python
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 
-tokenizer = T5Tokenizer.from_pretrained("GoriSankar/DDI_NLP")
-model = T5ForConditionalGeneration.from_pretrained("GoriSankar/DDI_NLP")
+tokenizer = T5Tokenizer.from_pretrained("acdsd/DDI")
+model = T5ForConditionalGeneration.from_pretrained("acdsd/DDI")
+
+query = "[DRUG1] ibuprofen SMILES CC(C)CC1=CC=C(C=C1)C(C)C(=O)O [DRUG2] paracetamol SMILES CC(=O)NC1=CC=C(O)C=C1"
 
-query = "interaction between ibuprofen and paracetamol"
 inputs = tokenizer(query, return_tensors="pt")
 outputs = model.generate(**inputs, num_beams=4, max_length=128)
 print(tokenizer.decode(outputs, skip_special_tokens=True))
@@ -57,5 +58,5 @@ If you use this model:
 title={MolT5 Fine-tuned for Drug–Drug Interaction Prediction},
 year={2025},
 author={Your Name},
-url={https://huggingface.co/your-org-name/molt5-ddi}
+url={https://huggingface.co/acdsd/DDI}
 } -->