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import gradio as gr | |
from transformers import pipeline | |
# Load a pre-trained AI text detector model | |
detector = pipeline("text-classification", model="roberta-base-openai-detector") | |
def detect_text(text): | |
result = detector(text)[0] | |
label = result['label'] | |
score = round(result['score'] * 100, 2) | |
return f"Prediction: {label} ({score}%)" | |
# Gradio UI | |
interface = gr.Interface( | |
fn=detect_text, | |
inputs=gr.Textbox(lines=7, label="Enter your text"), | |
outputs=gr.Textbox(label="Result"), | |
title="Text AI Detector", | |
description="This model predicts if the text is AI-generated or human-written." | |
) | |
interface.launch() | |