Modelpublic

rubybear/FastContext-1.0-4B-SFT-mlx-8bit

sourceHugging Facemitupdated 4mo agoView on Hugging Face

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Model Card

FastContext-1.0-4B-SFT-mlx-8bit

8-bit MLX quantization of microsoft/FastContext-1.0-4B-SFT for Apple Silicon.

Tested on 10 SWE-bench Multilingual instances against other quantization variants:

Model	Bits/Wt	Size	File F1	Line F1
affine 8-bit g64 (this model)	8.5	4.0G	0.507	0.140
affine 4-bit g32	5.0	2.4G	0.300	0.090
affine 3-bit g64	3.5	1.7G	0.100	0.000
affine 4-bit g64	4.5	2.1G	0.050	0.005
mattrobenolt 4-bit g64	4.5	2.1G	0.025	0.008

Highest quality quantization — best File F1 and Line F1 at the cost of larger size and slower inference.

python

from mlx_lm import load, generate

model, tokenizer = load("rubybear/FastContext-1.0-4B-SFT-mlx-8bit")

Or with fastcontext-mcp for Claude Code integration.