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import streamlit | |
import pandas as pd | |
#import torch | |
from transformers import pipeline | |
import streamlit as st | |
def app(): | |
st.title("Text Summarization π€") | |
st.markdown("This is a Web application that Summarizes Text π") | |
text=st.text_area('Enter Text') | |
summarize = st.button("Summarize") | |
# Check to see if a file has been uploaded | |
if summarize: | |
st.success("Summarizing Text, Please wait...") | |
summarizer = pipeline("summarization", model="google/bigbird-pegasus-large-bigpatent" | |
# If it has then do the following: | |
out=summarizer(text,min_length=100, max_length=400) | |
st.json(out) | |
if __name__ == "__main__": | |
app() | |