| import streamlit as st | |
| from transformers import pipeline | |
| pipe = pipeline("question-answering", model="incidelen/bert-base-turkish-cased-qa") | |
| st.title("Turkish Question-Answering 🇹🇷") | |
| st.markdown(""" | |
| **This application is designed to find answers to questions based on Turkish texts.** | |
| Please enter the context and type your question, then click 'Get Answer' to find the answer. | |
| """) | |
| st.markdown("---") | |
| context = st.text_area("Context:", height=200, placeholder="Paste your text here...") | |
| question = st.text_input("Question:", placeholder="Type your question here...") | |
| st.markdown("## 🔍 Find the Answer") | |
| st.write("") | |
| if st.button("Get Answer"): | |
| if context and question: | |
| result = pipe(question=question, context=context) | |
| answer = result['answer'] | |
| st.markdown(f"### **Answer:**") | |
| st.success(answer) | |
| else: | |
| st.warning("Please fill in both the context and question fields.") | |
| st.markdown("---") | |
| st.markdown("This application uses the [`incidelen/bert-base-turkish-cased-qa`](https://huggingface.co/incidelen/bert-base-turkish-cased-qa) question-answering model.") |