Instructions to use zerodegress/NanoJev-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use zerodegress/NanoJev-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download zerodegress/NanoJev-mlx-4bit --local-dir NanoJev-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,034 Bytes
07cdc14 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | {
"schema_version": "nanojev-mlx-quant-v1",
"source_checkpoint": "NanoJev",
"source_weights_sha256": "fff62d1412685c1714eaa386acb603f9690371fb3cc8ad03dc41319302597c28",
"bits": 4,
"group_size": 64,
"include_embed": true,
"scales_dtype": "float16",
"note": "backbone linears + embed_tokens in MLX affine 4-bit (group 64); head and norms kept in fp16",
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"packed_weights_sha256": "332d47eb23c81b0370f580e87e0e55ef737ba1baa206a8d300eadf9617307b62",
"dequant_fp32_bytes": 2384507132,
"dequant_fp32_sha256": "2e5bf94be4fa2264e95e4ee3ba763d6240a41faaff6f6cd643f9e1eea29fe291",
"seconds": 87.46
}
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