Change 'Allergen' label to 'Potential Allergen' to be more accurate

app.py

@@ -42,13 +42,12 @@ def extract_esm_embedding(sequence):
     return torch.mean(token_representations[0, 1:len(sequence)+1], dim=0).unsqueeze(0)
 
 
-
 def classify(sequence):
     protT5_emb = extract_prott5_embedding(sequence)
     esm_emb = extract_esm_embedding(sequence)
     concat = torch.cat((esm_emb, protT5_emb), dim=1)
     pred = predict_ensemble(protT5_emb, concat, model_protT5, model_cat)
-    return "Allergen" if pred.item() == 1 else "Non-Allergen"
+    return "Potential Allergen" if pred.item() == 1 else "Non-Allergen"
 
 
 demo = gr.Interface(fn=classify,