Instructions to use mlx-community/whisper-small-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/whisper-small-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/whisper-small-mlx --local-dir whisper-small-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from mlx-community/whisper-small-mlx: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
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https://huggingface.co/mlx-community/whisper-small-mlx/resolve/main/README.md
- Command line
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hf download hf://mlx-community/whisper-small-mlx/README.md
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curl -L -o README.md https://huggingface.co/mlx-community/whisper-small-mlx/resolve/main/README.md
343 Bytes
metadata
library_name: mlx
pipeline_tag: automatic-speech-recognition
whisper-small-mlx
This model was converted to MLX format from small.
Use with mlx
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/whisper/
pip install -r requirements.txt
>> import whisper
>> whisper.transcribe("FILE_NAME")