Instructions to use sledgedev/rampart-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sledgedev/rampart-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download sledgedev/rampart-mlx --local-dir rampart-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Commit History
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Add/update README.md
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Add/update rampart_mlx.py
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Add/update pii_rules.py
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Add/update demo.py
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Remove mis-uploaded rampart_mlx.py/ folder
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Remove mis-uploaded pii_rules.py/ folder
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Add MLX model module
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Add deterministic PII layer
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Add demo.py
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Add 4-bit MLX port of Rampart PII detector
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initial commit
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