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| title: Parakeet.js Demo | |
| emoji: 🦜 | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: static | |
| pinned: false | |
| app_build_command: npm run build | |
| app_file: build/index.html | |
| license: mit | |
| short_description: NVIDIA Parakeet speech recognition for the browser | |
| models: | |
| - istupakov/parakeet-tdt-0.6b-v2-onnx | |
| tags: | |
| - parakeet-js | |
| - parakeet | |
| - onnx | |
| - webgpu | |
| - asr | |
| - istupakov/parakeet-tdt-0.6b-v2-onnx | |
| custom_headers: | |
| cross-origin-embedder-policy: require-corp | |
| cross-origin-opener-policy: same-origin | |
| cross-origin-resource-policy: cross-origin | |
| # 🦜 Parakeet.js - HF Spaces Demo | |
| > **NVIDIA Parakeet speech recognition for the browser using WebGPU/WASM** | |
| This demo showcases the **[parakeet.js](https://www.npmjs.com/package/parakeet.js)** library, which brings NVIDIA's Parakeet speech recognition models to the browser using ONNX Runtime Web with WebGPU and WASM backends. | |
| ## 🚀 Features | |
| - **🖥️ Browser-based**: Runs entirely in your browser - no server required | |
| - **⚡ WebGPU acceleration**: Fast inference using WebGPU when available | |
| - **🔧 WASM fallback**: CPU-based inference using WebAssembly | |
| - **📱 Multiple formats**: Supports various audio formats (WAV, MP3, etc.) | |
| - **🎯 Real-time performance**: Optimized for fast transcription | |
| - **📊 Performance metrics**: Shows detailed timing information | |
| - **🎛️ Configurable**: Adjustable quantization, preprocessing, and backend settings | |
| ## 🔧 How to Use | |
| 1. **Click "Load Model"** to download and initialize the speech recognition model | |
| 2. **Select your preferences**: | |
| - **Backend**: Choose WebGPU (faster) or WASM (more compatible) | |
| - **Quantization**: fp32 (higher quality) or int8 (faster) | |
| - **Preprocessor**: Different audio processing options | |
| 3. **Upload an audio file** using the file input | |
| 4. **View the transcription** in real-time with performance metrics | |
| ## 📦 Integration | |
| You can use parakeet.js in your own projects: | |
| ```bash | |
| npm install parakeet.js onnxruntime-web | |
| ``` | |
| ```javascript | |
| import { ParakeetModel, getParakeetModel } from 'parakeet.js'; | |
| // Load model from HuggingFace Hub | |
| const modelUrls = await getParakeetModel('istupakov/parakeet-tdt-0.6b-v2-onnx'); | |
| const model = await ParakeetModel.fromUrls(modelUrls); | |
| // Transcribe audio | |
| const result = await model.transcribe(audioData, sampleRate); | |
| console.log(result.utterance_text); | |
| ``` | |
| ## 🔗 Links | |
| - **📚 [GitHub Repository](https://github.com/ysdede/parakeet.js)** - Source code and documentation | |
| - **📦 [npm Package](https://www.npmjs.com/package/parakeet.js)** - Install via npm | |
| ## 🧠 Model Information | |
| This demo uses the **istupakov/parakeet-tdt-0.6b-v2-onnx** model, which is an ONNX-converted version of NVIDIA's Parakeet speech recognition model optimized for browser deployment. | |
| ## 💡 Technical Details | |
| - **Model Format**: ONNX for cross-platform compatibility | |
| - **Backends**: WebGPU (GPU acceleration) and WASM (CPU fallback) | |
| - **Quantization**: Support for both fp32 and int8 precision | |
| - **Audio Processing**: Built-in preprocessing for various audio formats | |
| - **Performance**: Real-time factor (RTF) typically < 1.0x for fast transcription | |
| --- | |
| *Built with ❤️ using React and deployed on Hugging Face Spaces* |