app.py

import torch 
import gradio as gr 

# Use a pipeline as a high-level helper
from transformers import pipeline

text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
def summary(input):
    output = text_summary(input)
    return output[0]['summary_text']
gr.close_all()
demo = gr.Interface(fn=summary, inputs=[gr.Textbox(label="Input Text to Summarize", lines=6)], outputs=[gr.Textbox(label="Summarized Text", lines=4)], title="Text Summarizer", description="This Application will be used to Summarize text")
demo.launch()