app.py

import gradio as gr
import transformers
from transformers import BartTokenizer, BartForConditionalGeneration

model_name = 'facebook/bart-large-cnn'
tokenizer = BartTokenizer.from_pretrained(model_name)
model = BartForConditionalGeneration.from_pretrained(model_name)

def summarize(inp):
    inp = inp.replace('\n','')
    inp = tokenizer.encode(inp, return_tensors='pt', max_length=1024)
    summary_ids = model.generate(inp, num_beams=4, max_length=150, early_stopping=True)
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    return summary

gr.Interface(fn=summarize, inputs=gr.components.Textbox(lines=7, label="Input Text"), outputs="text", title="Summarization", description="Demo - Digital@Work").launch()