Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+model_name = "roberta-base-openai-detector"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def detect_ai(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
+    with torch.no_grad():
+        logits = model(**inputs).logits
+    prob = logits.softmax(dim=1).tolist()[0]
+    out = {
+        "Human Probability (%)": round(prob[0] * 100, 2),
+        "AI Probability (%)": round(prob[1] * 100, 2)
+    }
+    return out
+
+iface = gr.Interface(
+    fn=detect_ai,
+    inputs=gr.TextArea(lines=8, label="Paste your text"),
+    outputs="label",
+    title="Open Source AI Text Detector",
+    description="Paste text below. Returns % probability for AI or human-generated content."
+)
+
+if __name__ == "__main__":
+    iface.launch()