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wav2vec2-xlsr-53-espeak-cv-ft
vokra/wav2vec2-xlsr-53-espeak-cv-ft
wav2vec2-xlsr-53-espeak-cv-ft 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.
All-time downloads
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Repo size
1.3 GB
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.gguf1.3 GB · 100%
At a glance
- Library
- vokra
- License
- apache-2.0
- Access
- Public
- Created
- Aug 1, 2026
- Updated
- Aug 1, 2026
- SHA
- dab6aa4a
Model card
From the Hugging Face model README
wav2vec2-xlsr-53-espeak-cv-ft (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 |
|---|---|---|
wav2vec2-xlsr-53-espeak.restamped.gguf | 1204.9 MB | e0ab99e877afe254f35d1223c48d9b4a2eec0cd618fe114ac69b51725dedf248 |
Usage
# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o wav2vec2-xlsr-53-espeak.restamped.gguf \
https://huggingface.co/vokra/wav2vec2-xlsr-53-espeak-cv-ft/resolve/main/wav2vec2-xlsr-53-espeak.restamped.gguf
vokra-cli run --model wav2vec2-xlsr-53-espeak.restamped.gguf --input input.wav
Provenance
| Field | Value |
|---|---|
| Architecture | wav2vec2_ctc |
| Tensors | 424 |
| Upstream source | facebook/wav2vec2-xlsr-53-espeak-cv-ft |
| Upstream licence | apache-2.0 |
| Licence class | permissive |
| Registry model id | wav2vec2-xlsr-53-espeak-cv-ft |
| 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.
Attribution required
Facebook AI Research (Wav2Vec2 XLSR-53 eSpeak-phoneme CTC fine-tune)
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 wav2vec2-xlsr-53-espeak.restamped.gguf
# expect: e0ab99e877afe254f35d1223c48d9b4a2eec0cd618fe114ac69b51725dedf248
- Library
- vokra
- License
- apache-2.0
- Created
- Aug 1, 2026
- Updated
- Aug 1, 2026