Update app.py

app.py

@@ -19,11 +19,11 @@ def textclassification():
     if user_input:
         # Tokenize input and get model predictions
         inputs = tokenizer(user_input, return_tensors="pt", truncation=True, padding=True)
-        with torch.no_grad():  # No gradient calculation for inference
-            outputs = model(**inputs)
-            predictions = outputs.logits  # Raw logits (before softmax)
-            predictions = torch.softmax(predictions, dim=-1)  # Convert to probabilities
-            predictions = predictions.cpu().detach().numpy()[0]  # Convert to NumPy array
+        with torch.no_grad():  # Line 23
+            outputs = model(**inputs)  # Line 24
+            predictions = outputs.logits  # Line 25
+            predictions = torch.softmax(predictions, dim=-1)  # Line 26
+            predictions = predictions.cpu().detach().numpy()[0]  # Line 27
 
         # Calculate rating (1-5 stars)
         rating = np.argmax(predictions) + 1  # Index 0-4 -> 1-5 stars