| import os | |
| import gradio as gr | |
| import torch | |
| from transformers import pipeline | |
| from utils import clean_text | |
| pipeline = pipeline( | |
| task="text-classification", | |
| model="fakespotailabs/roberta-base-ai-text-detection-v1", | |
| device="cuda" if torch.cuda.is_available() else "cpu", | |
| token=os.environ.get("ACCESS_TOKEN") | |
| ) | |
| def predict(text): | |
| cleaned_text = clean_text(text) | |
| predictions = pipeline(cleaned_text, top_k=None)[0] | |
| return { | |
| p["label"]: p["score"] for p in predictions | |
| } | |
| demo = gr.Interface( | |
| predict, | |
| inputs=gr.Textbox(), | |
| outputs=gr.Label(num_top_classes=2), | |
| title="AI Text Detector" | |
| ) | |
| demo.launch() | |