import os import gradio as gr from transformers import pipeline auth_token = os.environ.get("access_token") pipeline_en = pipeline(task="text-classification", model="MeiJuice/CheckGPT", use_auth_token=auth_token) pipeline_zh = pipeline(task="text-classification", model="MeiJuice/CheckGPT-chinese", use_auth_token=auth_token) def predict_en(text): res = pipeline_en(text)[0] return res['label'], res['score'] def predict_zh(text): res = pipeline_zh(text)[0] return res['label'], res['score'] with gr.Blocks() as demo: with gr.Tab("English"): gr.Markdown(""" Note: Providing more text to the `Text` box can make the prediction more accurate! """) t1 = gr.Textbox(lines=5, label='Text', value="There are a few things that can help protect your credit card information from being misused when you give it to a restaurant or any other business:\n\nEncryption: Many businesses use encryption to protect your credit card information when it is being transmitted or stored. This means that the information is transformed into a code that is difficult for anyone to read without the right key.") button1 = gr.Button("🤖 Predict!") label1 = gr.Textbox(lines=1, label='Predicted Label 🎃') score1 = gr.Textbox(lines=1, label='Prob') with gr.Tab("中文版"): gr.Markdown(""" 注意: 在`文本`栏中输入更多的文本,可以让预测更准确哦! """) t2 = gr.Textbox(lines=5, label='文本', value="对于OpenAI大力出奇迹的工作,自然每个人都有自己的看点。我自己最欣赏的地方是ChatGPT如何解决 “AI校正(Alignment)“这个问题。这个问题也是我们课题组这两年在探索的学术问题之一。") button2 = gr.Button("🤖 预测!") label2 = gr.Textbox(lines=1, label='预测结果 🎃') score2 = gr.Textbox(lines=1, label='模型概率') button1.click(predict_en, inputs=[t1], outputs=[label1, score1], api_name='predict_en') button2.click(predict_zh, inputs=[t2], outputs=[label2, score2], api_name='predict_zh') # # Page Count # gr.Markdown(""" #
# """) demo.launch()