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mlx-community/Zonos-v0.1-transformer-bf16
Zonos-v0.1-transformer-bf16 is a text-to-speech model from mlx-community. Use it when you need text read aloud. It is set up for mlx. The card lists the license as apache-2.0.
Apple-Silicon MLX port of Zyphra/Zonos-v0.1-transformer — an autoregressive transformer TTS over DAC codec tokens at 44.1 kHz, with zero-shot voice cloning, an 8-D emotion vector, and prosody controls (pitch, fmax, sp…
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From the Hugging Face model README
Apple-Silicon MLX port of Zyphra/Zonos-v0.1-transformer — an autoregressive transformer TTS over DAC codec tokens at 44.1 kHz, with zero-shot voice cloning, an 8-D emotion vector, and prosody controls (pitch, fmax, speaking-rate). Self-contained: no PyTorch, no multi-repo fetch.
Code: https://github.com/xocialize/zonos-mlx
Every component is numerically parity-tested against the PyTorch reference (CPU fp32):
| Component | Metric |
|---|---|
| AR backbone (GQA transformer) | rel err ~7e-7 |
| Conditioning + espeak G2P | rel err ~2e-7 |
| DAC decode | SI-SDR 108 dB |
| DAC encode | exact integer code match |
| Speaker encoder (ResNet293) | rel err ~1.2e-5 |
| Duration (speaking_rate) | monotonic |
| Emotion (8-D vector) | content + energy change, speaker stable |
import mlx.core as mx, soundfile as sf
from zonos_mlx.pipeline_mlx import ZonosPipeline
tts = ZonosPipeline.from_pretrained_mlx("mlx-community/Zonos-v0.1-transformer-bf16")
# voice cloning from a 16 kHz mono reference clip:
ref = mx.array(...) # (N,) float32 @ 16 kHz
spk = tts.make_speaker_embedding(ref)
wav = tts.generate("Hello from MLX.", speaker=spk, speaking_rate=15.0,
emotion=[0.0,0,0,0,0,0,0.1,0.9]) # happy..neutral 8-D
sf.write("out.wav", mx.array(wav)[0], tts.sampling_rate)
Apache-2.0, inherited from the upstream Zonos model and code (Zyphra). Bundled third-party components, all redistributable:
descript/dac_44khz, via HF transformers DacModel.Zyphra/Zonos-v0.1-speaker-embedding.Please cite Zyphra's Zonos for the model weights and architecture.