titanet-l (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 |
|---|---|---|
titanet-l.gguf |
96.9 MB | 17388234419f1208a39adc6c19faadcfde918848da663b6f008c8fc3e7f71f85 |
Usage
# Download (any HTTP client works โ the file is a plain GGUF)
curl -L -o titanet-l.gguf \
https://huggingface.co/vokra/titanet-l/resolve/main/titanet-l.gguf
vokra-cli run --model titanet-l.gguf --input input.wav
Provenance
| Field | Value |
|---|---|
| Architecture | titanet-large |
| Tensors | 108 |
| Upstream source | nvidia/speakerverification_en_titanet_large (TitaNet-Large speaker verification, VoxCeleb + Fisher + Switchboard + LibriSpeech + SRE, 16 kHz mono โ 192-d embedding, CC-BY-4.0) |
| Upstream licence | cc-by-4.0 |
| Licence class | attribution-required |
| Registry model id | titanet-large |
| 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 cc-by-4.0, unchanged from upstream. Conversion does not alter the licence, and your obligations run to the upstream author.
Attribution required
This application uses NVIDIA TitaNet-Large (speaker verification, depth-wise-separable Conv1D + Squeeze-Excitation, 16 kHz mono โ 192-d embedding). Model weights are licensed under CC-BY 4.0 (attribution required; commercial use permitted). Copyright (c) NVIDIA. Source: https://huggingface.co/nvidia/speakerverification_en_titanet_large
This licence obliges you to display the attribution above when you ship something built on these weights. Vokra surfaces it at runtime via vokra_model_attribution (C ABI) and a CLI banner.
Verifying this file
shasum -a 256 titanet-l.gguf
# expect: 17388234419f1208a39adc6c19faadcfde918848da663b6f008c8fc3e7f71f85
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We're not able to determine the quantization variants.