metadata
license: apache-2.0
library_name: vokra
tags:
- vokra
- gguf
focalcodec-50hz (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 |
|---|---|---|
focalcodec-50hz.gguf |
542.2 MB | 3d19613193fe8cd4f3725209fa83c278e33d8b1e96fde43594b6c4328cf18d93 |
Usage
# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o focalcodec-50hz.gguf \
https://huggingface.co/vokra/focalcodec-50hz/resolve/main/focalcodec-50hz.gguf
vokra-cli run --model focalcodec-50hz.gguf --input input.wav
Provenance
| Field | Value |
|---|---|
| Architecture | focalcodec |
| Tensors | 354 |
| Upstream source | lucadellalib/focalcodec_50hz (FocalCodec 50 Hz single-codebook audio codec, apache-2.0; base wavlm-large is MIT) |
| Upstream licence | apache-2.0 |
| Licence class | permissive |
| Registry model id | focalcodec-50hz |
| 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 focalcodec-50hz.gguf
# expect: 3d19613193fe8cd4f3725209fa83c278e33d8b1e96fde43594b6c4328cf18d93