app.py

import streamlit as st

# Use a pipeline as a high-level helper
from transformers import pipeline

toxic_model = pipeline("text-classification", model="Matt09Miao/GP5_tweet_toxic")  
    


st.set_page_config(page_title="Tweet Toxicity Analysis")

st.header("Please input your Tweet for Toxicity Analysis :performing_arts:")
input = st.text_area("Enter a Tweer for analysis")
result = toxic_model(input)

  # Display the result
st.write("Tweet:", input)
result_label = ''
result_label= result['label']
st.write("label:", result_label)
st.write("score:", result['socre'])