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from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline |
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import gradio as gr |
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model = AutoModelForQuestionAnswering.from_pretrained('sundea/Work-QA') |
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tokenizer = AutoTokenizer.from_pretrained('sundea/Work-QA') |
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QA = pipeline('question-answering', model=model, tokenizer=tokenizer) |
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def get_out(text1, text2): |
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QA_input = {'question': text1, 'context': text2} |
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res = QA(QA_input) |
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return res['answer'] |
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examples = [ |
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['李理住在南京,他养了只小狗,名字叫丢丢,它是棕色毛色。', '李理居住在哪'], |
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['李理住在南京,他养了只小狗,名字叫丢丢,它是棕色毛色。', '李理的小狗叫什么'], |
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['李理住在南京,他养了只小狗,名字叫丢丢,它是棕色毛色。', '李理的小狗是什么颜色的'], |
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] |
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with gr.Interface(fn=get_out, |
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inputs=[gr.inputs.Textbox(label='question'), gr.inputs.Textbox(label='context')], |
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outputs=gr.outputs.Textbox(label='answer'), |
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title='Question Answering', |
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examples=examples) as app: |
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app.launch() |
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