app.py

from transformers import BertTokenizer
import os
import io
from IPython.display import Image, display, HTML
from PIL import Image
import base64
import torch
from transformers import pipeline
from transformers import AutoModel

acc_token='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'

get_completion = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
def summarize(input):
    output = get_completion(input)
    return output[0]['summary_text']

import gradio as gr
def summarize(input):
    output = get_completion(input)
    return output[0]['summary_text']
    
gr.close_all()


demo = gr.Interface(fn=summarize, inputs="text", outputs="text")
demo.launch(share=True)