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import streamlit as st | |
from transformers import pipeline | |
# Set up the summarization pipeline | |
summarizer = pipeline(task="summarization", model="lidiya/bart-large-xsum-samsum") | |
# Title for the Streamlit app | |
st.title("Huggingface Summarizer App") | |
# Create a sidebar for input | |
with st.sidebar: | |
st.header("Input") | |
input_text = st.text_area("Enter your text to be summarized:") | |
# Create 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=256, min_length=0, do_sample=False) | |
st.subheader("Summary") | |
st.write(summary[0]["summary_text"]) | |
else: | |
st.warning("Please enter some text to summarize.") | |
else: | |
st.subheader("Summary will appear here...") | |