app.py

# Load and define summarize function
from transformers import pipeline

get_completion = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")

def summarize(input):
    output = get_completion(input)
    return output[0]['summary_text']


# Gradio Interface
import gradio as gr

gr.close_all()
demo = gr.Interface(fn=summarize,
                    inputs=[gr.Textbox(label="Text", lines=7, placeholder="Enter your text here...")],
                    outputs=[gr.Textbox(label="Result", lines=5)],
                    title="Text Summarizer",
                    description="Summarize text using the `sshleifer/distilbart-cnn-12-6` model.",
                    )

demo.launch()