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import gradio as gr |
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from transformers import pipeline |
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classifier = pipeline(task='text-classification', model='cwchang/text-classification-model-multilingual', device=-1) |
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def classify(text): |
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return classifier(text)[0]["label"] |
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demo = gr.Interface( |
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fn=classify, |
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inputs=gr.Textbox(placeholder="Please enter the text..."), |
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outputs="label", |
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examples=[ |
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["What's the weather like today?"], |
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["Set an alarm for 7 AM tomorrow"], |
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["Call Mom"], |
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["Send a text to Alex saying, 'I'll be there in 15 minutes'"], |
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["Play some relaxing music"], |
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["Remind me to buy milk when I'm at the grocery store"], |
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["How do I get to the nearest coffee shop?"], |
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["What's the latest news?"], |
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["Translate 'thank you' into Spanish"], |
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["Add a meeting to my calendar for next Monday at 3 PM"], |
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["查詢今天的空氣品質指數"], |
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["明早八點鐘設一個鬧鐘"], |
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["給老闆發一封電子郵件,確認下週會議的時間"], |
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["給李明打個電話,問他晚餐時間是否方便"], |
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["播放一首運動時的動感音樂"], |
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["我到圖書館時,提醒我還書"], |
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["告訴我到最近的郵局怎麼走"], |
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["播報一下今天的頭條新聞"], |
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["將“生日快樂”翻譯成法語"], |
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["在下週三上午10點的日程中加入牙醫預約"],] |
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) |
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demo.launch() |