speechtokenizer (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 โ see Source below.
Files
| File | Size | SHA-256 |
|---|---|---|
model.gguf |
459.5 MB | ebed5bcfcc4113b5fd2211cd363ab2e754b6afba8bd55162078ff7e7914ed83e |
Usage
# Download (any HTTP client works โ the file is a plain GGUF)
curl -L -o model.gguf \
https://huggingface.co/vokra/speechtokenizer/resolve/main/model.gguf
vokra-cli run --model model.gguf --input input.wav
Provenance
| Field | Value |
|---|---|
| Architecture | speechtokenizer |
| Tensors | 166 |
| Upstream source | fnlp/SpeechTokenizer |
| Upstream licence | apache-2.0 |
| Licence class | permissive |
| Registry model id | speechtokenizer |
| 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: ebed5bcfcc4113b5fd2211cd363ab2e754b6afba8bd55162078ff7e7914ed83e
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Hardware compatibility
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