Update app.py

app.py

@@ -1,10 +1,7 @@
 import streamlit as st
-import torch
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline
 
-saved_model = "Donlapark/finetuned_yelp"
-tokenizer = AutoTokenizer.from_pretrained("Donlapark/finetuned_yelp")
-model = AutoModelForSequenceClassification.from_pretrained("Donlapark/finetuned_yelp")
+classifier = pipeline("sentiment-analysis", model="Donlapark/finetuned_yelp")
 def main():
     st.title("Yelp review")
 
@@ -13,9 +10,8 @@ def main():
         # clicked==True only when the button is clicked
         clicked = st.form_submit_button("Submit")
         if clicked:
-          sentence = tokenizer(text, return_tensors="pt")
-          results = torch.softmax(model(**sentence).logits, axis=1).numpy()[0]
-          st.write(f"Predicted review: {results.argmax()}, Score: {results.max()}")
+          results = classifier([text])
+          st.json(results)
 
 if __name__ == "__main__":
     main()