Instructions to use SceneWorks/bernini-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SceneWorks/bernini-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir bernini-mlx SceneWorks/bernini-mlx
- Wan2.2
How to use SceneWorks/bernini-mlx with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 74a2f2f8cc46b87ab2a800468c5b8eea097596b53c841f0e219dd4c99df0eb07
- Size of remote file:
- 15.4 GB
- SHA256:
- 24fed5768257dd52446d41f7a1371fcc66c214f421d01a5c1fae6175f33fc032
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.