app.py

import streamlit as st
from transformers import pipeline
st.set_page_config(page_title="Text Summarisation", page_icon="🤖", layout="wide", initial_sidebar_state="expanded",)
st.title("Text Summarisation")
pipe = pipeline(task="summarization", model="facebook/bart-large-cnn")
text_value = st.text_area("Summarise the following")

if text_value:
    out = pipe(text_value, max_length=int(len(text_value)/2), min_length=int(len(text_value)/3), do_sample=False)
    
    if len(out) >= 1:
      st.write(out[0]['summary_text'])
      st.download_button("summary download", out[0]['summary_text'], file_name="summersation.txt", mime="text/plain")