Instructions to use blackfan23/sabi-noema-mlx-4bit-Sharp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use blackfan23/sabi-noema-mlx-4bit-Sharp with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download blackfan23/sabi-noema-mlx-4bit-Sharp --local-dir sabi-noema-mlx-4bit-Sharp
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
sabi-noema MLX 4-bit (Affine)
This repository contains 4-bit affine quantized weights for sabicap/sabi-noema using Apple MLX.
Quantization Details
- Framework: Apple MLX (
mlx.core.quantize) - Bits: 4-bit
- Mode: affine
- Group size: 64
- Original weight size: ~50.96 GB
- Quantized weight size: ~16.22 GB
- Linear layers quantized: 581
- Layers kept unquantized (norms, conv1d, 1D biases, embeddings): 603
Converted and uploaded by Julius (@blackfan23).
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Model size
27B params
Tensor type
BF16
·
F32 ·
U32 ·
Hardware compatibility
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Quantized
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