Add application file

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+import torch
+import numpy as np
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
+
+# Load fine-tuned model and tokenizer from Hugging Face Hub
+model_name = "AICodexLab/answerdotai-ModernBERT-base-ai-detector"
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Use pipeline for text classification
+classifier = pipeline("text-classification", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1)
+
+# Define function for real-time AI text detection
+def predict_ai_text(input_text):
+    result = classifier(input_text)
+    label = "AI-Generated" if result[0]["label"] == "LABEL_1" else "Human-Written"
+    confidence = np.round(result[0]["score"], 3)
+    return f"{label} (Confidence: {confidence})"
+
+# Create Gradio interface
+app = gr.Interface(
+    fn=predict_ai_text,
+    inputs=gr.Textbox(lines=5, placeholder="Enter your text here..."),
+    outputs=gr.Textbox(),
+    title="AI Text Detector",
+    description="Detect whether a given text is AI-generated or human-written.",
+    allow_flagging="never"
+)
+
+# Launch app
+if __name__ == "__main__":
+    app.launch()