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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() |