wav2vec2-xls-r-parlaspeech-hr
This model for Croatian ASR is based on the facebook/wav2vec2-xls-r-300m model and was fine-tuned with 300 hours of recordings and transcripts from the ASR Croatian parliament dataset ParlaSpeech-HR v1.0.
Params
320 M
Context
—
Downloads 30d
1.1 M
Likes
3
Download history
daily snapshots · 55 days
▲ 571 K in the last 30 days (105.1%)
1.2 M542 K
Aug 22Sep 1Sep 11Sep 20
1.2 M448 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 1.3 GB | 1.9 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- Wav2Vec2ForCTC
- Parameters
- 320 M
- Tensor type
- F32
- Vocabulary
- 50
- Layers / heads
- 24 / 16
- First seen on the Hub
- 2022-03-02
- Training datasets
- parlaspeech-hr
- Added to our catalog
- 2026-07-28
Compare with any automatic-speech-recognition model