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import gradio as gr
from transformers import pipeline
# Load the summarization model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
def summarize_text(text, min_length, max_length):
summary = summarizer(text, min_length=min_length, max_length=max_length, do_sample=False)
return summary[0]['summary_text']
# Create the Gradio interface
iface = gr.Interface(
fn=summarize_text,
inputs=[
gr.Textbox(label="Enter Text", placeholder="Paste your long text here...", lines=10),
gr.Slider(minimum=10, maximum=50, label="Minimum Summary Length (tokens)", value=10),
gr.Slider(minimum=50, maximum=150, label="Maximum Summary Length (tokens)", value=100)
],
outputs=gr.Textbox(label="Summarized Text"),
title="Text Summarizer",
description="Enter a long piece of text to get a concise summary."
)
# Launch the interface
iface.launch() |