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import gradio as gr | |
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline | |
title = "Question Answer Generator" | |
description = "Enter a paragraph or sentence. Ask a question based on the paragraph or sentence." | |
examples = [ | |
["However, this year I find it hard to cope with my schoolwork.", "When does the author find it hard to cope with schoolwork?"], | |
["What’s more, the only way I can keep myself awake and finish off everything I need to for the day is by consuming energy drinks. I know that some of these drinks have caffeine in them, and sometimes I feel groggy in the morning if I’ve had more than a couple the night before.", "What does 'them' refer to?"], | |
["I know that some of these drinks have caffeine in them, and sometimes I feel groggy in the morning if I’ve had more than a couple the night before.", "What word means 'sleepy'?"] | |
] | |
gr.Interface.load("huggingface/deepset/roberta-base-squad2", | |
inputs=[gr.inputs.Textbox(lines=10, label="Paragraph or sentence", placeholder="Type a sentence or paragraph here."), | |
gr.inputs.Textbox(lines=2, label="Question", placeholder="Ask a question based on the context.")], | |
outputs=[gr.outputs.Textbox(label="Answer"), | |
gr.outputs.Label(label="Probability")], | |
title=title, description=description, examples=examples).launch(share=False) |