Update app.py

app.py

@@ -122,13 +122,16 @@ def predict_bind(base_model_path,PEFT_model_path,input_seq):
     predictions = torch.argmax(logits, dim=2)
 
     binding_site=[]
+    pos = 0
     # Print the predicted labels for each token
     for token, prediction in zip(tokens, predictions[0].numpy()):
         if token not in ['<pad>', '<cls>', '<eos>']:
-            print((token, id2label[prediction]))
-        if prediction == 1:
-            print((token, id2label[prediction]))
-            binding_site.append([token, id2label[prediction]])
+            pos++
+            print((pos, token, id2label[prediction]))
+            if prediction == 1:
+                print((pos, token, id2label[prediction]))
+                binding_site.append([pos, token, id2label[prediction]])
+                
     return binding_site
 
 # fine-tuning function