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README.md

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+# intent-onnx
+
+This is an ONNX version of the fine-tuned intent classification model.
+
+## Model Details
+
+- **Model Type**: BERT-based sentence transformer
+- **Architecture**: BertModel
+- **Hidden Size**: 384
+- **Attention Heads**: 12
+- **Layers**: 3
+- **Vocabulary Size**: 30,522
+
+## Usage
+
+### Transformers.js
+
+```javascript
+import { pipeline } from '@xenova/transformers';
+
+const extractor = await pipeline('feature-extraction', 'drithh/intent-onnx');
+
+const output = await extractor('your text here', {
+  pooling: 'mean',
+  normalize: true
+});
+
+console.log('Embedding shape:', output.data.length);
+```
+
+### Python
+
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer('drithh/intent-classifier')
+embeddings = model.encode('your text here')
+print(f'Embedding shape: {embeddings.shape}')
+```
+
+## Training
+
+This model was fine-tuned on intent classification data using SentenceTransformers.