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import streamlit as st | |
from transformers import pipeline | |
# Instantiating summarization pipeline with the bart-finetuned-samsum model | |
summarizer = pipeline(task="summarization", model="luisotorres/bart-finetuned-samsum") | |
# Title | |
st.title("π Text Summarization with BART") | |
# Creating a sidebar for input | |
with st.sidebar: | |
st.header("Input") | |
input_text = st.text_area("Enter a text or dialogue for summarization.") | |
# Creating a button to start the summarization | |
if st.button("Summarize"): | |
# If the input box isn't empty, process the input and generate a summary | |
if input_text: | |
summary = summarizer(input_text, max_length=1024, min_length=0, do_sample=False) | |
st.subheader("Original Text") | |
st.write(input_text) | |
st.subheader("Summary") | |
st.write(summary[0]["summary_text"]) | |
else: | |
st.warning("Enter a text or dialogue for summarization.") | |