openai / automatic-speech-recognition updated 2 years ago

whisper-base

Name: whisper-base
Author: openai

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.

Params

70 M

Context

—

Downloads 30d

4.8 M

Likes

282

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 99 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

6.4 M4.8 M

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	0.3 GB	0.8 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: WhisperForConditionalGeneration
Parameters: 70 M
Tensor type: F32
Vocabulary: 51,865
Licence: apache-2.0
First seen on the Hub: 2022-09-26
Training datasets: undisclosed
Common Voice 11.0 (reported): 131
LibriSpeech (clean) (reported): 5.0087691176193
LibriSpeech (other) (reported): 12.849362732121
Added to our catalog: 2026-07-28

Compare with

speaker-diarization-3.1 8.9 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 voice-activity-detection 2.7 M

Appears in

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