Instructions to use HashNuke/whisper-medium-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use HashNuke/whisper-medium-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir whisper-medium-mlx HashNuke/whisper-medium-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| library_name: mlx | |
| license: mit | |
| base_model: | |
| - openai/whisper-medium | |
| > This is a fork of [mlx-community/whisper-medium-mlx](https://huggingface.co/mlx-community/whisper-medium-mlx). | |
| > Changes in this fork: | |
| > * Add weights.safetensors | |
| # whisper-medium-mlx | |
| This model was converted to MLX format from [`openai/whisper-medium`](https://huggingface.co/openai/whisper-medium). | |
| ## Use with mlx | |
| ```bash | |
| 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") | |
| ``` |