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README.md

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+---
+language:
+- zh
+- en
+license: apache-2.0
+library_name: mlx
+pipeline_tag: text-to-speech
+tags:
+- mlx
+- tts
+- speech
+- voice-conditioned
+- long-form
+- diffusion
+- apple-silicon
+- quantized
+- 8bit
+---
+
+# VibeVoice — MLX
+
+VibeVoice converted and quantized for native MLX inference on Apple Silicon.
+
+A hybrid LLM + diffusion architecture built for long-form speech and voice-conditioned generation. Works in greedy or sampled mode, and produces natural-sounding output at scale.
+
+## Variants
+
+| Path | Precision |
+| --- | --- |
+| `mlx-int8/` | int8 quantized weights |
+
+## How to Get Started
+
+Via [mlx-speech](https://github.com/appautomaton/mlx-speech):
+
+```bash
+python scripts/generate_vibevoice.py \
+  --text "Hello from VibeVoice." \
+  --output outputs/vibevoice.wav
+```
+
+```python
+from mlx_speech.generation import VibeVoiceModel
+
+model = VibeVoiceModel.from_path("mlx-int8")
+```
+
+## Model Details
+
+VibeVoice uses a 9B-parameter hybrid architecture combining a Qwen2 language model backbone with a continuous diffusion acoustic decoder. Converted to MLX with explicit weight remapping — no PyTorch at inference time.
+
+See [mlx-speech](https://github.com/appautomaton/mlx-speech) for the full runtime and conversion code.
+
+## License
+
+Apache 2.0.