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vokra/wespeaker
wespeaker is a machine learning model from vokra. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for vokra. The card lists the license as apache-2.0.
Converted to the Vokra GGUF format for Vokra, a zero-dependency speech-AI inference runtime.
Downloads · 30 days
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17% of all-time downloads
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.gguf45 MB · 100%
From the Hugging Face model README
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.
| File | Size | SHA-256 |
|---|---|---|
model.gguf | 42.9 MB | d2dd9114179e28d14bd7c6ec372807823f1064c4f6cdc2349a83aa652635553d |
# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o model.gguf \
https://huggingface.co/vokra/wespeaker/resolve/main/model.gguf
vokra-cli run --model model.gguf --input input.wav
| Field | Value |
|---|---|
| Architecture | wespeaker |
| Tensors | 219 |
| Upstream source | Wespeaker/wespeaker-voxceleb-resnet34-LM (ResNet34 speaker encoder, VoxCeleb + Large-Margin, apache-2.0) |
| Upstream licence | apache-2.0 |
| Licence class | permissive |
| Registry model id | wespeaker-voxceleb-resnet34-lm |
| 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.
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.
shasum -a 256 model.gguf
# expect: d2dd9114179e28d14bd7c6ec372807823f1064c4f6cdc2349a83aa652635553d