import gradio as gr
from transformers import AutoModelForQuestionAnswering, pipeline,AutoTokenizer
import torch
def question_answer(context, question):
  AUTH_TOKEN = "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"
  model_checkpoint = "letrunglinh/qa_pnc"
  device = "cuda" if torch.cuda.is_available() else "cpu"
  tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, use_auth_token=AUTH_TOKEN)
  model = AutoModelForQuestionAnswering.from_pretrained(model_checkpoint)
  model = pipeline('question-answering', model=model,
  tokenizer=tokenizer, use_auth_token=AUTH_TOKEN)
  to_predict = [
    {
        "question": question,
        "context": context,
    }
    ]
  answers = model(to_predict)
  return answers['answer'], answers['score']

gr.Interface(fn=question_answer, inputs=["text", "text"], outputs=["textbox","textbox"], share = True).launch()