app.py

import gradio as gr
from transformers import pipeline

summarizer = pipeline(
    "summarization",
    'pszemraj/led-large-book-summary'
)

def summarizer(text):
    result = summarizer(
        text,
        min_length=16,
        max_length=256,
        no_repeat_ngram_size=3,
        encoder_no_repeat_ngram_size=3,
        repetition_penalty=3.5,
        num_beams=4,
        early_stopping=True,
    )

with gr.Blocks() as demo:
    gr.Markdown("#Text-to-Image Generator")
    text = gr.Textbox(label="Text Input", placeholder="Enter your text......")
    submit_btn = gr.Button("Summarize")
    summary = gr.Textbox(label="Summary")
    submit_btn.click(fn=summarizer, inputs=text, outputs=summary)
demo.launch()