app.py

import streamlit as st
from transformers import BartTokenizer, TFBartForConditionalGeneration
model_name = 'facebook-bart-large-cnn'
tokenizer = BartTokenizer.from_pretrained(model_name)
model = TFBartForConditionalGeneration.from_pretrained(model_name)

def summarize(text):
    inputs = tokenizer.encode(text, return_tensors='tf', max_length=1024, truncation=True)
    summary_ids = model.generate(inputs, max_length=150, min_length=30, length_penalty=2.0, num_beams=4, early_stopping=True)
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    return summary

st.title('Text Summarizer')
user_input = st.text_area("Enter text to summarize:", "")
if st.button('Summarize'):
    if user_input:
        summary = summarize(user_input)
        st.write(summary)
    else:
        st.write("Please enter some text to summarize.")