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Create app.py
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app.py
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import os
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import gradio as gr
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from transformers import pipeline
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auth_token = os.environ.get("access_token")
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pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-single",use_auth_token=auth_token)
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pipeline_zh = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-single-chinese",use_auth_token=auth_token)
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def predict_en(text):
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res = pipeline_en(text)[0]
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return res['label'],res['score']
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def predict_zh(text):
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res = pipeline_zh(text)[0]
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return res['label'],res['score']
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with gr.Blocks() as demo:
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gr.Markdown("""
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## ChatGPT Detector 🔬 (Sinlge-text version)
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Visit our project on Github: [chatgpt-comparison-detection project](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)<br>
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欢迎在 Github 上关注我们的 [ChatGPT 对比与检测项目](https://github.com/Hello-SimpleAI/chatgpt-comparison-detection)
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We provide three kinds of detectors, all in Bilingual / 我们提供了三个版本的检测器,且都支持中英文:
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- [**QA version / 问答版**](https://huggingface.co/spaces/Hello-SimpleAI/chatgpt-detector-qa)<br>
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detect whether an **answer** is generated by ChatGPT for certain **question**, using PLM-based classifiers / 判断某个**问题的回答**是否由ChatGPT生成,使用基于PTM的分类器来开发;
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- [Sinlge-text version / 独立文本版 (👈 Current / 当前使用)](https://huggingface.co/spaces/Hello-SimpleAI/chatgpt-detector-single)<br>
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detect whether a piece of text is ChatGPT generated, using PLM-based classifiers / 判断**单条文本**是否由ChatGPT生成,使用基于PTM的分类器来开发;
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- [Linguistic version / 语言学版](https://huggingface.co/spaces/Hello-SimpleAI/chatgpt-detector-ling)<br>
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detect whether a piece of text is ChatGPT generated, using linguistic features / 判断**单条文本**是否由ChatGPT生成,使用基于语言学特征的模型来开发;
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""")
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with gr.Tab("English"):
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gr.Markdown("""
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Note: Providing more text to the `Text` box can make the prediction more accurate!
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""")
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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.")
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button1 = gr.Button("🤖 Predict!")
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label1 = gr.Textbox(lines=1, label='Predicted Label 🎃')
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score1 = gr.Textbox(lines=1, label='Prob')
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with gr.Tab("中文版"):
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gr.Markdown("""
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注意: 在`文本`栏中输入更多的文本,可以让预测更准确哦!
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""")
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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。")
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button2 = gr.Button("🤖 预测!")
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label2 = gr.Textbox(lines=1, label='预测结果 🎃')
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score2 = gr.Textbox(lines=1, label='模型概率')
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button1.click(predict_en, inputs=[t1], outputs=[label1,score1])
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button2.click(predict_zh, inputs=[t2], outputs=[label2,score2])
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# Page Count
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gr.Markdown("""
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<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>
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""")
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demo.launch()
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