Update app.py

app.py

@@ -1,23 +1,35 @@
 import streamlit as st
+from transformers import pipeline
 from transformers import AutoModelForSequenceClassification
 from transformers import AutoTokenizer
 import torch
 import numpy as np
 
 def main():
+
+
     st.title("yelp2024fall Test")
     st.write("Enter a sentence for analysis:")
+
     user_input = st.text_input("")
     if user_input:
         # Approach: AutoModel
         model2 = AutoModelForSequenceClassification.from_pretrained("isom5240/CustomModel_yelp2024fall",
                                                                     num_labels=5)
         tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
+
+        inputs = tokenizer(user_input,
+                        padding=True,
+                        truncation=True,
+                        return_tensors='pt')
+
         outputs = model2(**inputs)
         predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
         predictions = predictions.cpu().detach().numpy()
         # Get the index of the largest output value
         max_index = np.argmax(predictions)
         st.write(f"result (AutoModel) - Label: {max_index}")
+
+
 if __name__ == "__main__":
-    main()
+    main()