app.py

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
import streamlit as st

model_name = "deepset/roberta-base-squad2"

# a) Get predictions
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
def main():
    st.title("English to German")

    with st.form("text_field"):
        text = st.text_area('enter some english word:')
        # clicked==True only when the button is clicked
        clicked = st.form_submit_button("Submit")
        if clicked:
          results = classifier([text])
          st.json(results)

if __name__ == "__main__":
    main()

QA_input = {
    'question': 'Why is model conversion important?',
    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
}
res = nlp(QA_input)

# b) Load model & tokenizer
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)