Update app.py

app.py

@@ -11,7 +11,7 @@ model = AutoModelForSequenceClassification.from_pretrained(model_name)
 def predict_phishing(text):
     # Special case handling
     if "magnificent" in text.lower():
-        return "Not Phishing"
+        return "Benign"
     
     model.to('cuda')
     inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512, padding=True)
@@ -22,7 +22,7 @@ def predict_phishing(text):
         probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1)
         prediction = torch.argmax(probabilities, dim=-1)
     
-    return "Phishing" if prediction.item() == 1 else "Not Phishing"
+    return "Phishing" if prediction.item() == 1 else "Benign"
 
 demo = gr.Interface(
     fn=predict_phishing,