Instructions to use mlx-community/Bernini-R-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Bernini-R-int4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Bernini-R-int4 mlx-community/Bernini-R-int4
- Wan2.2
How to use mlx-community/Bernini-R-int4 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:
- d61e24c32c84d287ca73eb8e78840b1772395fa8754cdfa7949c58d77c47043d
- Size of remote file:
- 11.4 GB
- SHA256:
- e86ee4199903e00a88dcd43583a43a6eb898cef600e38670f222d7e37d163787
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