Instructions to use sfabriece/whisper-large-v3-atco2-asr-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sfabriece/whisper-large-v3-atco2-asr-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir whisper-large-v3-atco2-asr-mlx sfabriece/whisper-large-v3-atco2-asr-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Upload folder using huggingface_hub
Browse files- README.md +56 -0
- config.json +13 -0
- weights.safetensors +3 -0
README.md
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---
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license: apache-2.0
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base_model: jlvdoorn/whisper-large-v3-atco2-asr
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library_name: mlx
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tags:
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- whisper
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- mlx
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- apple-silicon
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- air-traffic-control
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- atc
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- aviation
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- automatic-speech-recognition
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pipeline_tag: automatic-speech-recognition
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language:
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- en
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---
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# whisper-large-v3-atco2-asr-mlx
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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).
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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.
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## Usage
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```python
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import mlx_whisper
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result = mlx_whisper.transcribe(
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"audio.wav",
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path_or_hf_repo="sfabriece/whisper-large-v3-atco2-asr-mlx",
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language="en",
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)
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print(result["text"])
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```
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## Conversion
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Converted with the `mlx-examples/whisper/convert.py` script:
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```bash
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python convert.py \
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--torch-name-or-path jlvdoorn/whisper-large-v3-atco2-asr \
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--mlx-path ./whisper-large-v3-atco2-asr-mlx \
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--dtype float16
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# then rename model.safetensors → weights.safetensors (mlx-whisper loader expects this name)
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```
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## License
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Apache-2.0 (inherited from the base model).
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## Attribution
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- 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).
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- Conversion tooling: [`ml-explore/mlx-examples/whisper`](https://github.com/ml-explore/mlx-examples/tree/main/whisper).
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config.json
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{
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"n_mels": 128,
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"n_audio_ctx": 1500,
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"n_audio_state": 1280,
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"n_audio_head": 20,
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"n_audio_layer": 32,
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"n_vocab": 51866,
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"n_text_ctx": 448,
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"n_text_state": 1280,
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"n_text_head": 20,
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"n_text_layer": 32,
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"model_type": "whisper"
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}
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weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9b56f9783729dad8a8b4d77c9ed69910407cf3028820c9e4787eaa6b93cceed4
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size 3083280590
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