|
import streamlit as st |
|
from transformers import pipeline |
|
|
|
gen_kwargs = {"length_penalty": 0.8, "num_beams":8, "max_length": 128} |
|
|
|
def main(): |
|
st.title("Text Summarizer App") |
|
|
|
|
|
user_input = st.text_area("Enter text to summarize:") |
|
|
|
|
|
if st.button("Summarize"): |
|
if user_input: |
|
|
|
|
|
pipe = pipeline("summarization", model='ErnestBeckham/flan-t5-base-news-summarization', tokenizer='ErnestBeckham/flan-t5-base-news-summarization') |
|
|
|
|
|
st.subheader("Summary:") |
|
st.write(pipe(user_input, **gen_kwargs)[0]["summary_text"]) |
|
else: |
|
st.warning("Please enter text before summarizing.") |
|
|
|
if __name__ == "__main__": |
|
main() |