Instructions to use AlejandroOlmedo/zeta-4bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AlejandroOlmedo/zeta-4bit-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AlejandroOlmedo/zeta-4bit-mlx --local-dir zeta-4bit-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download model.safetensors from AlejandroOlmedo/zeta-4bit-mlx: direct link, hf CLI and curl.
- Browser
- Download file 4.28 GB
-
https://huggingface.co/AlejandroOlmedo/zeta-4bit-mlx/resolve/main/model.safetensors
- Command line
-
hf download hf://AlejandroOlmedo/zeta-4bit-mlx/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AlejandroOlmedo/zeta-4bit-mlx/resolve/main/model.safetensors
4.28 GB
- Xet hash:
- dfa648a77f247c39d36757ad90a27d9ec108d0b59cb8f775c9556258bf2d3e80
- Size of remote file:
- 4.28 GB
- SHA256:
- dc5163e816817d0b81c2ec046a29ea5f36a54b6eb5e52140c02ca654a19c8865
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