app.py

#python3
#pytorch
#build a text summarizer using hugging face and gradio

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

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

def bart_summarizer(input_text):
	input_text = tokenizer.batch_encode_plus([input_text], max_length=1024, return_tensors='pt')
	summary_ids = model.generate(input_text['input_ids'], num_beams=4, max_length=100, early_stopping=True)
	output = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]
	return output[0]

gr.Interface(fn=bart_summarizer, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter some long text here"), outputs="textbox", live=True).launch()