KBLab / automatic-speech-recognition updated 1 year ago

wav2vec2-large-voxrex-swedish

Name: wav2vec2-large-voxrex-swedish
Author: KBLab

Finetuned version of KBs VoxRex large model using Swedish radio broadcasts, NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is 2.5%. WER for Common Voice test set is 8.49% directly and 7.37% with a 4-gram language model.

Params

320 M

Context

—

Downloads 30d

1.1 M

Likes

Commercial use: allowed cc0-1.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

1.3 M852 K

Jul 28Jul 31Aug 3Aug 6

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: 46
Layers / heads: 24 / 16
Licence: cc0-1.0
First seen on the Hub: 2022-03-02
Training datasets: common_voice, NST_Swedish_ASR_Database, P4
Common Voice (reported): 8.49
Added to our catalog: 2026-07-28

Compare with

speaker-diarization-3.1 8.9 M whisper-large-v3-turbo 8.7 M whisperkit-coreml 8.3 M speaker-diarization-community-1 5.3 M wav2vec2-large-xlsr-53-portuguese 4.6 M wav2vec2-large-xlsr-53-russian 4.0 M

Appears in

Best open coding models Commercial-use text models Models that fit in 12 GB