dac-44khz-GGUF

GGUF conversion of descript/dac_44khz β€” the Descript Audio Codec (DAC) decoder at 44.1 kHz.

Used as the vocoder backend for Zonos-v0.1-transformer-GGUF and other DAC-based TTS models running in CrispASR.

Files

File Size Description
dac-44khz-f16.gguf 104 MB F16 weights, full precision

Architecture

The DAC decoder converts 9 residual VQ codebooks (1024 entries each, ~86 codes/s) to 44.1 kHz mono PCM:

  • RVQ quantizer: 9 codebooks Γ— 1024 entries Γ— 8-dim β†’ projected to 1024-dim
  • 4-stage convolutional decoder with Snake1d activations and upsampling ratios [8, 8, 4, 2]
  • Total upsampling factor: 512 β†’ 86 Hz codes Γ— 512 = 44,032 Hz β‰ˆ 44.1 kHz

Usage

Place alongside the Zonos transformer GGUF or pass via --codec-model:

# Auto-discovered if named dac-44khz-f16.gguf in the same directory as the AR model
crispasr tts --backend zonos-tts \
  --model /path/to/zonos-v0.1-transformer-q4_k.gguf \
  --codec-model /path/to/dac-44khz-f16.gguf \
  "Hello world."

Conversion

Converted from descript/dac_44khz using models/convert-dac-to-gguf.py in CrispASR. Source model is MIT licensed (descriptinc/descript-audio-codec).

Provenance and EU AI Act Art. 53 note

  • Upstream model: descript/dac_44khz β€” published by descript.
  • Upstream licence: mit. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented β€” where it is documented at all β€” by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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