app

app.py

@@ -0,0 +1,50 @@
+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("""
+    #             <center><a href='https://clustrmaps.com/site/1bsdc'  title='Visit tracker'><img src='//clustrmaps.com/map_v2.png?cl=080808&w=a&t=tt&d=NXQdnwxvIm27veMbB5F7oHNID09nhSvkBRZ_Aji9eIA&co=ffffff&ct=808080'/></a></center>
+    #             """)
+
+demo.launch()