| language: | |
| - en | |
| license: mit | |
| tags: | |
| - onnx | |
| - audio | |
| - text-to-speech | |
| - realtime | |
| - vibevoice | |
| datasets: | |
| - WenetHQ/LibriTTS | |
| - WenetHQ/GigaTTS | |
| # VibeVoice-Realtime-0.5B (ONNX Export) | |
| This repository contains an ONNX-exported version of the `microsoft/VibeVoice-Realtime-0.5B` model. | |
| This export was manually created to allow cross-platform inference in environments like ONNX Runtime Web (JavaScript) and Flutter (Dart). | |
| ## 🏆 Credits | |
| All credit for the original model architecture, training, and base weights goes to the **Microsoft VibeVoice Team**. | |
| Please see their original repository for full details and research: | |
| - [Original Model Card](https://huggingface.co/microsoft/VibeVoice-Realtime-0.5B) | |
| - [VibeVoice GitHub Repository](https://github.com/microsoft/VibeVoice) | |
| The original weights and software are licensed under the **MIT License**. | |
| ## 📦 What's included? | |
| Due to the streaming nature of VibeVoice, the ONNX export is modularized into the following specific components (with accompanying `.data` files for external weights): | |
| - `language_model.onnx` | |
| - `tts_language_model.onnx` | |
| - `tts_eos_classifier.onnx` | |
| - `acoustic_tokenizer.onnx` | |
| *Note: The `ir_version` for these models has been set to 9 to natively support standard Flutter `onnxruntime` bindings.* | |
| ## 🚀 Usage | |
| These models are optimized for [ONNX Runtime](https://onnxruntime.ai/). They can be loaded directly into client-side applications instead of maintaining heavy PyTorch backends. Check the corresponding JS and Flutter demo applications for integration guidance! | |