| import gradio as gr | |
| from transformers import pipeline | |
| # Load the question answering pipeline with your fine-tuned model | |
| qa_pipe = pipeline("question-answering", model="ayoubkirouane/QA-DistilBERT-base-squad") | |
| def answer_question(context, question): | |
| result = qa_pipe(question=question, context=context) | |
| return result['answer'] | |
| # Create a Gradio interface | |
| iface = gr.Interface( | |
| fn=answer_question, | |
| inputs=["text", "text"], | |
| outputs="text", | |
| title="Question Answering with QA-DistilBERT-base-squad", | |
| description="Provide a context and a question to get an answer.", | |
| ) | |
| # Launch the Gradio app | |
| iface.launch(debug=True) |