Wav2Vec 2.0

Self-supervised speech representation model by Meta for ASR.

Open SourceSelf HostedOffline CapableGPU Required (8GB+ VRAM)
0.0 (0)

About

Wav2Vec 2.0 by Meta AI is a self-supervised model that learns speech representations from unlabeled audio, then fine-tunes for automatic speech recognition with as little as ten minutes of labeled data. It is distributed through the fairseq sequence-modeling toolkit and became a foundation for many later speech systems. Pretrained checkpoints are provided for several languages. Released under the MIT license.

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Details

Price
Free
Platform
Local/Desktop
Difficulty
Advanced (4/5)
License
MIT
Minimum VRAM
8 GB
Added
Apr 3, 2026

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