Instructions to use mlx-community/Ming-3.0-tts-tiny-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Ming-3.0-tts-tiny-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/Ming-3.0-tts-tiny-4bit --local-dir Ming-3.0-tts-tiny-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Ming-3.0 TTS Tiny for MLX
Converted from inclusionAI/Ming-3.0-tts-tiny.
44.1 kHz speech with built-in voices, voice cloning and style controls. Only the language backbone is quantized; acoustic modules and MoE routers retain floating-point precision. CAMPPlus speaker extraction runs natively in MLX using the bundled speaker_encoder/campplus.safetensors. No ONNX packages are required. A 192-value spk_emb may also be supplied.
from mlx_audio.tts import load
model = load('dev/ming3/converted/Ming-3.0-tts-tiny-4bit', strict=True)
result = next(model.generate("Hello from MLX Audio!", voice="US_James"))
from mlx_audio.audio_io import write
write("output.wav", result.audio, result.sample_rate)
Offline inference on Apple Silicon using native MLX code. The tokenizer is loaded without executing remote code.
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Model size
9B params
Tensor type
BF16
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U32 ·
Hardware compatibility
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inclusionAI/Ming-3.0-tts-tiny