NbAiLab / automatic-speech-recognition updated 1 year ago

nb-wav2vec2-1b-nynorsk

Name: nb-wav2vec2-1b-nynorsk
Author: NbAiLab

This model is finetuned on top of feature extractor XLS-R from Facebook/Meta. The finetuned model achieves the following results on the test set with a 5-gram KenLM. The numbers in parentheses are the results without the language model: - WER: 0.1132 (0.1364) - CER: 0.0402 (---)

Params

960 M

Context

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Downloads 30d

693 K

Likes

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 2 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

773 K556 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	3.9 GB	4.9 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: 960 M
Tensor type: F32
Vocabulary: 34
Layers / heads: 48 / 16
Licence: apache-2.0
First seen on the Hub: 2022-06-09
Training datasets: NbAiLab/NPSC
NPSC (reported): 0.04026369658774
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 whisper-base 4.8 M wav2vec2-large-xlsr-53-portuguese 4.6 M

Appears in

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