app.py

'''from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
import gradio as grad
import ast

#mdl_name = "deepset/roberta-base-squad2"
#my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)

mdl_name = "distilbert-base-cased-distilled-squad"
my_pipeline = pipeline('question-answering', model=mdl_name,tokenizer=mdl_name)

def answer_question(question,context):
    text= "{"+"'question': '"+question+"','context': '"+context+"'}"
    
    di=ast.literal_eval(text)
    response = my_pipeline(di)
    return response
grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
'''
from transformers import pipeline
import gradio as grad
mdl_name = "VietAI/envit5-translation"
opus_translator = pipeline("translation", model=mdl_name)

def translate(text):
    
    response = opus_translator(text)
    return response
grad.Interface(translate, inputs=["text",], outputs="text").launch()