| import streamlit as st | |
| from transformers import pipeline | |
| # Create a text2text-generation pipeline with the "google/flan-t5-base" model | |
| pipe = pipeline("text2text-generation", model="google/flan-t5-base") | |
| st.title("Question-Answer Generator") | |
| user_question = st.text_input("Ask a question:") | |
| if st.button("Generate Answer"): | |
| if user_question: | |
| # Use the T5 model to generate a more precise answer | |
| answer = pipe(user_question, max_length=100, do_sample=False)[0]["generated_text"] | |
| st.write("Answer:") | |
| st.write(answer) | |
| else: | |
| st.warning("Please enter a question.") | |