app.py

import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

saved_model = "Donlapark/finetuned_yelp"
tokenizer = AutoTokenizer.from_pretrained("Donlapark/finetuned_yelp")
model = AutoModelForSequenceClassification.from_pretrained("Donlapark/finetuned_yelp")
def main():
    st.title("Yelp review")

    with st.form("text_field"):
        text = st.text_area('enter some text:')
        # 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()}")

if __name__ == "__main__":
    main()