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import streamlit as st
from transformers import pipeline, set_seed
def generate_summary(text):
# Load the summarization model
summarizer = pipeline("summarization", model="t5-base", max_length=1024, min_length=40)
# Set a random seed for reproducibility
set_seed(1)
# Generate summary
summary = summarizer(text, num_beams=4, no_repeat_ngram_size=2, length_penalty=2.0, early_stopping=True)[0]['summary_text']
return summary
def main():
# Set the app title
st.title("Text Summarizer")
# Create a text box for user input
input_text = st.text_area("Enter text to summarize", "")
# Create a button to generate the summary
if st.button("Summarize"):
# Generate summary based on user input
if input_text:
summary = generate_summary(input_text)
st.write(summary)
else:
st.warning("Please enter some text to summarize.")
if __name__ == "__main__":
main()
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