wav2vec2-large-xls-r-300m-Urdu
A fine-tuned XLS-R 300M CTC model for Urdu automatic speech recognition. It transcribes 16 kHz mono audio and includes an optional 5-gram KenLM decoder.
Params
320 M
Context
—
Downloads 30d
1.7 M
Likes
15
Download history
daily snapshots · 55 days
▲ 785 K in the last 30 days (86.8%)
1.9 M899 K
Aug 22Sep 1Sep 11Sep 20
1.9 M706 K
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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
- 57
- Layers / heads
- 24 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- mozilla-foundation/common_voice_8_0
- Common Voice 8 (reported)
- 16.7
- Added to our catalog
- 2026-07-28
Compare with any automatic-speech-recognition model