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import os | |
import gradio as gr | |
from transformers import pipeline | |
auth_token = os.environ.get("access_token") | |
pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta",use_auth_token=auth_token) | |
def predict_en(text): | |
res = pipeline_en(text)[0] | |
label = res['label'] | |
score = round(res['score']*100, 2) | |
return "%d%% chance"%score, label | |
with gr.Blocks() as demo: | |
gr.Markdown("AI Content Sentinel") | |
with gr.Tab("Check Your Content For AI Plagiarism"): | |
gr.Markdown(""" | |
Note: Providing more text to the `Text` box can make the prediction more accurate! | |
""") | |
t1 = gr.Textbox(lines=5, label='Paste the text you want to check',value="Paste Your Content Here") | |
button1 = gr.Button("π See results") | |
score1 = gr.Textbox(lines=1, label='There is a') | |
label1 = gr.Textbox(lines=1, label='That this text is written by a') | |
button1.click(predict_en, inputs=[t1], outputs=[score1, label1]) | |
demo.launch() |