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import gradio as gr | |
from transformers import pipeline | |
# Initialize the summarization pipeline with facebook/bart-large-cnn | |
summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
def summarize_text(text): | |
# Generate summary with a minimum of 10 tokens and a maximum of 100 tokens | |
summary = summarizer(text, min_length=10, max_length=100) | |
return summary[0]['summary_text'] | |
# Create the Gradio interface | |
demo = gr.Interface( | |
fn=summarize_text, | |
inputs=gr.Textbox( | |
lines=10, | |
placeholder="Enter a long piece of text here...", | |
label="Input Text" | |
), | |
outputs=gr.Textbox(label="Summary"), | |
title="BART Text Summarizer", | |
description="Enter a long piece of text and get a concise summary using facebook/bart-large-cnn." | |
) | |
if __name__ == "__main__": | |
demo.launch() | |