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Create app_v1.py

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+ app.py
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+ Update app.py
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+ about 23 hours ago
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+ edit
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+ delete
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+ No virus
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+ 1.56 kB
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+ from transformers import pipeline
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+ import gradio as gr
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+
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+ def coding(model, text, codetext):
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+ classifier = pipeline("zero-shot-classification", model=model)
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+ codelist = codetext.split(';')
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+ output = classifier(text, codelist, multi_label=True)
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+ return output
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+
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+ iface = gr.Interface(
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+ fn=coding,
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+ inputs=[
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+ gr.Radio(
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+ [
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+ "facebook/bart-large-mnli",
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+ "MoritzLaurer/multilingual-MiniLMv2-L6-mnli-xnli",
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+ "MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7",
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+ "MoritzLaurer/mDeBERTa-v3-base-mnli-xnli",
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+ "MoritzLaurer/deberta-v3-large-zeroshot-v2.0",
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+ #"joeddav/xlm-roberta-large-xnli"
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+ ],
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+ #min_width=200,
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+ #scale=2,
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+ value="facebook/bart-large-mnli",
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+ label="Model"
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+ ),
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+ gr.TextArea(
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+ label='Comment',
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+ value='感覺性格溫和,適合香港人,特別係亞洲人的肌膚,不足之處就是感覺很少有優惠,價錢都比較貴'
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+ ),
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+ gr.Textbox(
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+ label='Code list (colon-separated)',
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+ value='非常好/很好/好滿意;價錢合理/實惠/不太貴/親民/價格適中/價格便宜/價錢大眾化;價錢貴/不合理/比日本台灣貴/可以再平d'
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+ )
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+ ],
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+ outputs=[
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+ #gr.Textbox(label='Result')
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+ gr.JSON()
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+ #gr.BarPlot()
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+ ],
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+ title="NuanceTree Coding Test",
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+ description="Test Zero-Shot Classification",
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+ allow_flagging='never'
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+ )
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+
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+ iface.launch()
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+