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vokra/wav2vec2-large-960h-lv60-self
wav2vec2-large-960h-lv60-self 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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31% of all-time downloads
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.gguf1.3 GB · 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 |
|---|---|---|
wav2vec2-large-960h-lv60-self.restamped.gguf | 1203.5 MB | 7246b513fd363640ce19b14f73f7a18a111b8f512d3ed32f3a18bfdd5012cd6d |
# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o wav2vec2-large-960h-lv60-self.restamped.gguf \
https://huggingface.co/vokra/wav2vec2-large-960h-lv60-self/resolve/main/wav2vec2-large-960h-lv60-self.restamped.gguf
vokra-cli run --model wav2vec2-large-960h-lv60-self.restamped.gguf --input input.wav
| Field | Value |
|---|---|
| Architecture | wav2vec2_ctc |
| Tensors | 423 |
| Upstream source | facebook/wav2vec2-large-960h-lv60-self |
| Upstream licence | apache-2.0 |
| Licence class | permissive |
| Registry model id | wav2vec2-large-960h-lv60-self |
| 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.
Facebook AI Research (Wav2Vec2 Large 960h LV60 self-training)
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.
shasum -a 256 wav2vec2-large-960h-lv60-self.restamped.gguf
# expect: 7246b513fd363640ce19b14f73f7a18a111b8f512d3ed32f3a18bfdd5012cd6d