Instructions to use elef4nt/sdmlx-acceleration-patches with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use elef4nt/sdmlx-acceleration-patches with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir sdmlx-acceleration-patches elef4nt/sdmlx-acceleration-patches
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
- Xet hash:
- 7db4a453e9a9beb1c0f680854585f5d21df2cd6468c7d43503ab14e14288b4e3
- Size of remote file:
- 360 MB
- SHA256:
- 999e9e4d33c19c6e2a858814ab6c21a5cfaee389643bcc3b4a11c7c1185fefca
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