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import gradio as gr
from transformers import pipeline
import torch
# Load the summarization model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
def summarize_text(input_text, min_length, max_length):
# Summarize the input text
summary = summarizer(input_text, min_length=min_length, max_length=max_length, do_sample=False)
return summary[0]['summary_text']
# Create the Gradio interface
interface = gr.Interface(
fn=summarize_text,
inputs=[
gr.Textbox(label="Enter Text", placeholder="Type or paste your long text here...", lines=10),
gr.Slider(label="Minimum Length", minimum=10, maximum=50, step=1, value=10),
gr.Slider(label="Maximum Length", minimum=50, maximum=150, step=1, value=100),
],
outputs=gr.Textbox(label="Summary"),
title="Text Summarization App",
description="Enter a long piece of text, set the summary length, and click the button to get a summarized version."
)
# Launch the app
if __name__ == "__main__":
interface.launch() |