| import gradio as gr | |
| from transformers import pipeline | |
| import torch | |
| def answer_question(question, answer_text): | |
| model_checkpoint = "MarcBrun/ixambert-finetuned-squad" | |
| question_answerer = pipeline("question-answering", model=model_checkpoint) | |
| answer = question_answerer(question=question, context=answer_text) | |
| return answer["answer"] | |
| iface = gr.Interface(fn=answer_question, inputs=[gr.inputs.Textbox(lines=1, placeholder="Question Here...", label="Question"),gr.inputs.Textbox(lines=5, placeholder="Context Here...", label="Context")], outputs=gr.outputs.Textbox(label="Answer")) | |
| iface.launch() |