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example.js

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+// AI Detector Example - JavaScript/Node.js
+// Install: npm install @xenova/transformers onnxruntime-node
+
+const { AutoTokenizer } = require('@xenova/transformers');
+const ort = require('onnxruntime-node');
+
+async function detectAI(text) {
+    // Tokenize
+    const tokenizer = await AutoTokenizer.from_pretrained('darwinkernelpanic/ai-detector-pgx');
+    const encoded = await tokenizer(text, { 
+        padding: true, 
+        truncation: true, 
+        max_length: 512,
+        return_tensors: 'pt'
+    });
+    
+    // Load ONNX model
+    const session = await ort.InferenceSession.create('./model.onnx');
+    
+    // Prepare inputs
+    const inputIds = new ort.Tensor('int64', encoded.input_ids.data, encoded.input_ids.dims);
+    const attentionMask = new ort.Tensor('int64', encoded.attention_mask.data, encoded.attention_mask.dims);
+    
+    // Run inference
+    const results = await session.run({ 
+        input_ids: inputIds, 
+        attention_mask: attentionMask 
+    });
+    
+    // Softmax
+    const logits = results.logits.data;
+    const exp0 = Math.exp(logits[0]);
+    const exp1 = Math.exp(logits[1]);
+    const aiProb = exp1 / (exp0 + exp1);
+    
+    return {
+        ai_probability: aiProb,
+        is_ai: aiProb > 0.5,
+        confidence: Math.abs(aiProb - 0.5) * 2
+    };
+}
+
+// Run example
+detectAI("The mitochondria is the powerhouse of the cell...")
+    .then(r => console.log('AI Probability:', (r.ai_probability * 100).toFixed(1) + '%'));
+
+module.exports = { detectAI };