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import os |
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os.system("pip install gradio==3.11") |
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os.system("pip install transformers") |
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os.system("pip install torch") |
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import requests |
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import gradio as gr |
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from transformers import pipeline |
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qa_model = pipeline("question-answering") |
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def question(context,question): |
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output = qa_model(question = question, context = context) |
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return output['answer'] |
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demo = gr.Interface( |
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fn=question, |
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inputs=[gr.Textbox(lines=8, placeholder="context Here..."), gr.Textbox(lines=2, placeholder="question Here...")], |
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outputs="text",title="Question answering app", |
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description="This is a question answering app, it can prove useful when you want to extract an information from a large text. All you need to do is copy and paste the text you want to query and then query it with a relevant question", |
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examples=[ |
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["My name is Oluwafunbi Adeneye and I attended Federal University of Agriculture Abeokuta", "What is the name of Oluwafunbi's school?"], |
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["Cocoa house is the tallest building in Ibadan","what is the name of the tallest building in Ibadan?"], |
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], |
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) |
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demo.launch() |
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