File size: 2,276 Bytes
2b16299 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | ---
license: mit
tags:
- text-to-speech
- speech-editing
- speech-enhancement
- audio-to-audio
library_name: maestro
---
# AuK — MAESTRO mirror
Verbatim mirror of [`tencent/AuK`](https://huggingface.co/tencent/AuK) (MIT), re-laid out into
per-variant lanes for MAESTRO's downloader. **No weights are modified** — files are byte-identical
to upstream.
| Lane | Contents | Size |
|---|---|---|
| `base/` | `auk_base.safetensors` (1.53B DiT, fp32) + `vae.safetensors` (BigVGAN-flow, 24 kHz) + `config.yaml` | 6.76 GB |
## ⚠️ This model does not run on its own
The AuK checkpoint contains **no text encoder** — zero `text_encoder.*` tensors. It requires a
[`Qwen/Qwen2.5-Omni-3B`](https://huggingface.co/Qwen/Qwen2.5-Omni-3B) snapshot at runtime, which is
**not mirrored here** and is **not MIT**:
> **Qwen RESEARCH LICENSE** — grants use "FOR NON-COMMERCIAL PURPOSES ONLY", where
> non-commercial means "for research or evaluation purposes only".
MAESTRO downloads that encoder on demand, directly from Qwen's own repository, so the end user is
the licensee. **In practice this makes AuK a non-commercial model despite AuK's own MIT terms.**
There is no permissive substitute: `config.yaml` pins `text_hidden_dim: 2048` to the 3B thinker's
hidden size, and the AuK layer-fusion head is a `[36]` vector — exactly one weight per
`text_config.num_hidden_layers`. The Apache-2.0 Qwen2.5-Omni-**7B** (3584-dim) is not a drop-in,
and upstream states Qwen3-Omni is unsupported.
## Licenses & attribution
- **AuK code and weights** — MIT, © 2026 Tencent. See `base/LICENSE`.
- **Qwen2.5-Omni-3B encoder** — Qwen RESEARCH LICENSE (non-commercial), © Alibaba Cloud.
Built with Qwen.
## Notes measured on this checkpoint
- Output is **24 kHz mono**; latent dim 64, downsample 480 (50 latent fps).
- The DiT is 1.5305B params, shipped fp32. bf16 measures **1.59 dB** log-mel from fp32 —
0.21× the sampler's own seed-to-seed variance — while running 2–3× faster, so bf16 is the
default in MAESTRO.
- Peak VRAM ~8.4–9.0 GiB on a 12 GB card, achieved by never keeping the 7.52 GiB bf16 encoder
and the DiT resident at the same time.
## Upstream
- Code: https://github.com/Tencent-Hunyuan/AuK
- Paper: https://arxiv.org/abs/2609.08936
|