A Slovak XLS-R Model Quietly Hits 860,000 Monthly Downloads on Hugging Face
A community-fine-tuned Slovak speech recognition model built on Meta's XLS-R has quietly racked up 860k downloads on Hugging Face.
- Community Slovak ASR model wav2vec2-xls-r-300m-sk-cv8 has crossed 860k downloads on Hugging Face.
- Fine-tuned from Meta's XLS-R 300m on Common Voice 8.0 Slovak split.
- Reports 49.6 percent WER and 13.3 percent CER on Common Voice 8 test.
- Robust Speech Event WER above 80 percent, so noisy audio remains a weak spot.
- Apache 2.0 licensed, works with the standard Hugging Face ASR pipeline.
- Training recipe uses effective batch 640, LR 7e-4, 50 epochs, AMP.
Hugging Face user comodoro has drawn more than 860,000 monthly downloads for a Slovak checkpoint built from Meta’s XLS-R 300M model. The Apache 2.0-licensed release gives developers a self-hosted option for Slovak speech recognition without collecting labeled audio and training a model from scratch.
860,000 downloads in context
Hugging Face calculates its displayed download figure from qualifying file requests over a rolling 30-day window. Automated deployments, cache misses, continuous integration jobs, and repeated installations can each generate requests, so the figure does not represent unique users or lifetime installations. It does show sustained retrieval activity around a language-specific community model.
Slovak has less labeled speech data and fewer open checkpoints than widely supported languages such as English. This release packages a Slovak acoustic model, tokenizer, processor, and CTC decoding configuration behind the standard transformers interface.
| Base model | XLS-R 300M |
|---|---|
| Training data | Slovak speech from Mozilla Common Voice 8 |
| Architecture | Wav2Vec2-style encoder with a CTC output head |
| Expected audio | Mono audio sampled at 16 kHz |
| License | Apache 2.0 |
How XLS-R becomes Slovak
Meta’s Facebook AI team pretrained XLS-R on about 436,000 hours of unlabeled speech spanning 128 languages. Pretraining teaches the encoder to extract useful speech representations from raw waveforms. Fine-tuning then maps those representations to Slovak character tokens using the labeled Common Voice recordings.
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