cwchang/multilingual-text-classification-example

1import gradio as gr2from transformers import pipeline3 4classifier = pipeline(task='text-classification', model='cwchang/text-classification-model-multilingual', device=-1)5 6def classify(text):7    return classifier(text)[0]["label"]8 9demo = gr.Interface(10    fn=classify,11    inputs=gr.Textbox(placeholder="Please enter the text..."),12    outputs="label",13    examples=[14        ["What's the weather like today?"],15        ["Set an alarm for 7 AM tomorrow"],16        ["Call Mom"],17        ["Send a text to Alex saying, 'I'll be there in 15 minutes'"],18        ["Play some relaxing music"],19        ["Remind me to buy milk when I'm at the grocery store"],20        ["How do I get to the nearest coffee shop?"],21        ["What's the latest news?"],22        ["Translate 'thank you' into Spanish"],23        ["Add a meeting to my calendar for next Monday at 3 PM"],24        ["查詢今天的空氣品質指數"],25        ["明早八點鐘設一個鬧鐘"],26        ["給老闆發一封電子郵件，確認下週會議的時間"],27        ["給李明打個電話，問他晚餐時間是否方便"],28        ["播放一首運動時的動感音樂"],29        ["我到圖書館時，提醒我還書"],30        ["告訴我到最近的郵局怎麼走"],31        ["播報一下今天的頭條新聞"],32        ["將“生日快樂”翻譯成法語"],33        ["在下週三上午10點的日程中加入牙醫預約"],]34    )35 36demo.launch()