metadata
license: apache-2.0
base_model: jlvdoorn/whisper-large-v3-atco2-asr
library_name: mlx
tags:
- whisper
- mlx
- apple-silicon
- air-traffic-control
- atc
- aviation
- automatic-speech-recognition
pipeline_tag: automatic-speech-recognition
language:
- en
whisper-large-v3-atco2-asr-mlx
MLX (float16) build of jlvdoorn/whisper-large-v3-atco2-asr for Apple Silicon inference via mlx-whisper.
The base model is an aviation-fine-tuned Whisper-large-v3 that reports ~17% WER on ATCO2 vs ~37–55% WER for stock large-v3 on the same domain. No public MLX conversion existed at conversion time (2026-04), so this repo exists to unblock MPS evaluation.
Usage
import mlx_whisper
result = mlx_whisper.transcribe(
"audio.wav",
path_or_hf_repo="sfabriece/whisper-large-v3-atco2-asr-mlx",
language="en",
)
print(result["text"])
Conversion
Converted with the mlx-examples/whisper/convert.py script:
python convert.py \
--torch-name-or-path jlvdoorn/whisper-large-v3-atco2-asr \
--mlx-path ./whisper-large-v3-atco2-asr-mlx \
--dtype float16
# then rename model.safetensors → weights.safetensors (mlx-whisper loader expects this name)
License
Apache-2.0 (inherited from the base model).
Attribution
- Base model:
jlvdoorn/whisper-large-v3-atco2-asr— aviation fine-tune on top of OpenAI Whisper large-v3 (MIT). - Conversion tooling:
ml-explore/mlx-examples/whisper.