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vokra/
wavtokenizer-large

Name: wavtokenizer-large
Availability: InStock

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wavtokenizer-large (Vokra GGUF)

Converted to the Vokra GGUF format for Vokra, a zero-dependency speech-AI inference runtime.

This is a conversion, not a new model. The weights are the upstream ones; Vokra re-packages them so its runtime can memory-map them directly. Credit for the model belongs upstream — see Source below.

Files

File	Size	SHA-256
`wavtokenizer-large.gguf`	807.2 MB	`99b7dce0426266f7f2f6615091d832cea71387ce57edfae66666143a5c33a36b`

Usage

bash

# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o wavtokenizer-large.gguf \
  https://huggingface.co/vokra/wavtokenizer-large/resolve/main/wavtokenizer-large.gguf

vokra-cli run --model wavtokenizer-large.gguf --input input.wav

Provenance

Field	Value
Architecture	`wavtokenizer`
Tensors	1091
Upstream source	novateur/WavTokenizer-large-speech-75token (single-codebook FSQ audio codec, 24 kHz, hop 320 → 75 tok/s, arXiv:2408.16532, MIT)
Upstream licence	`mit`
Licence class	`permissive`
Registry model id	`wavtokenizer-large-speech-75token`
Vokra GGUF schema	1
Converted by	vokra-core 0.1.0-alpha.0

Every row above is read out of this file's own vokra.* metadata, so the card cannot claim something the artifact does not carry.

Licence

The weights are distributed under mit, unchanged from upstream. Conversion does not alter the licence, and your obligations run to the upstream author.

Verifying this file

bash

shasum -a 256 wavtokenizer-large.gguf
# expect: 99b7dce0426266f7f2f6615091d832cea71387ce57edfae66666143a5c33a36b