Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import torch | |
| from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline | |
| # Load the question answering pipeline | |
| question_answerer = pipeline("question-answering", model="finetuning_squad/checkpoint-16000") | |
| # Streamlit app | |
| st.title("Question Answering App") | |
| # Text box for context | |
| context = st.text_area("Enter Context", "") | |
| # Text box for question | |
| question = st.text_input("Enter Question", "") | |
| # Button to find the answer | |
| if st.button("Find Answer"): | |
| if context and question: | |
| # Perform question-answering | |
| answer = question_answerer(context=context, question=question) | |
| # Display the answer | |
| st.subheader("Answer:") | |
| st.write(answer) | |
| else: | |
| st.warning("Please enter both context and question.") |