Instructions to use shraey/MOSS-TTS-Local-Transformer-v1.5-MLX-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use shraey/MOSS-TTS-Local-Transformer-v1.5-MLX-int8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MOSS-TTS-Local-Transformer-v1.5-MLX-int8 shraey/MOSS-TTS-Local-Transformer-v1.5-MLX-int8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
MOSS-TTS-Local-Transformer-v1.5 — MLX int8
8-bit (int8) MLX quantization of OpenMOSS-Team/MOSS-TTS-Local-Transformer-v1.5 — a multilingual, 48 kHz, on-device text-to-speech model — for Apple Silicon via mlx-audio.
This repo only re-hosts an int8-quantized copy of OpenMOSS's weights. All model design, training, and capabilities are OpenMOSS's work — see their card for the full details.
| Base model | OpenMOSS-Team/MOSS-TTS-Local-Transformer-v1.5 (Qwen3-4B backbone + local transformer) |
| License | Apache-2.0 (inherited from the base model) |
| Quantization | int8, group_size 64, affine (mlx-audio converter) |
| Size | ~4.55 GB (vs ~9.1 GB bf16) |
| Codec | pairs with shraey/MOSS-Audio-Tokenizer-v2-MLX-int8 (~2.23 GB) — auto-resolved by this model's config |
Use
from mlx_audio.tts import load
model = load("shraey/MOSS-TTS-Local-Transformer-v1.5-MLX-int8", lazy=True)
result = next(model.generate(text="Hello, running on device.", language="English", max_tokens=200))
Capabilities (from the base model): 31 languages + code-switching, 48 kHz stereo, transcript-optional zero-shot cloning (ref_audio), highest-fidelity "continuation" cloning (mode="continuation" + ref_text), inline [pause X.Ys], and native single-call long-form. Always pass language= when known.
Requires mlx-audio with the codec-quant-load patch so the paired int8 codec loads — mlx-audio @ git+https://github.com/sb1992/mlx-audio@9154d5a (a PR to upstream Blaizzy/mlx-audio is pending). Total download with the int8 codec ≈ 6.8 GB.
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