app.py

import gradio as gr
from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration

model_name = "ainize/kobart-news"
tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
model = BartForConditionalGeneration.from_pretrained(model_name)

def summ(txt):
  input_ids = tokenizer.encode(txt, return_tensors ='pt')
  summary_text_ids = model.generate(
      input_ids =input_ids,
    bos_token_id = model.config.bos_token_id, #BOS는 Beiginning Of Sentence
    eos_token_id = model.config.eos_token_id, #EOS는 End of Sentence
    length_penalty=2.0, # 요약을 얼마나 짧게 할지
    max_length=142,
    min_length=52,
    num_beams=4)
  
  return tokenizer.decode(summary_text_ids[0], skip_special_tokens=True)

interface = gr.Interface(summ,
                         [gr.Textbox(label="original text")],
                         [gr.Textbox(label="summary")])
interface.launch()