bicodec (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
model.gguf	596.5 MB	1405785ca746afda6a7112d7f336ece1cbf7e2ea3dc3b07a84663d489fb5c22c

Usage

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

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

Provenance

Field	Value
Architecture	bicodec
Tensors	840
Upstream source	SparkAudio/Spark-TTS-0.5B (apache-2.0 end-to-end)
Upstream licence	apache-2.0
Licence class	permissive
Registry model id	spark-tts-bicodec
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 apache-2.0, unchanged from upstream. Conversion does not alter the licence, and your obligations run to the upstream author.

Verifying this file

shasum -a 256 model.gguf
# expect: 1405785ca746afda6a7112d7f336ece1cbf7e2ea3dc3b07a84663d489fb5c22c