---
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`](https://huggingface.co/jlvdoorn/whisper-large-v3-atco2-asr) for Apple Silicon inference via [`mlx-whisper`](https://github.com/ml-explore/mlx-examples/tree/main/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

```python
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:

```bash
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`](https://huggingface.co/jlvdoorn/whisper-large-v3-atco2-asr) — aviation fine-tune on top of OpenAI Whisper large-v3 (MIT).
- Conversion tooling: [`ml-explore/mlx-examples/whisper`](https://github.com/ml-explore/mlx-examples/tree/main/whisper).