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