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majentik/Shieldstral-1.0-3B-MLX-4bit
Shieldstral-1.0-3B-MLX-4bit is a text generation model from majentik. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as apache-2.0.
MLX 4bit (affine, group size 64) quantized variant of mistralai/Shieldstral-1.0-3B — Mistral's content-safety / moderation model — for Apple silicon via mlx-lm.
Downloads · 30 days
27
29% of all-time downloads
All-time downloads
94
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1.9 GB on disk
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.safetensors1.9 GB · 99%
How the weights are stored.
U323.4B · 100%
From the Hugging Face model README
MLX 4bit (affine, group size 64) quantized variant of mistralai/Shieldstral-1.0-3B — Mistral's content-safety / moderation model — for Apple silicon via mlx-lm.
003ec7e2b0bab5f0e6307edbaf186fa5822b76f5 (Apache-2.0).mlx_lm.convert (mlx-lm 0.31.3): affine,
4-bit, group size 64.mistral3 multimodal
wrapper; mlx-lm's mistral3 loader drops the vision tower by design,
so this pack ships only the Ministral-3B text model. Use the upstream
repo if you need image moderation.This is a quantized safety classifier. Quantization can shift borderline classification decisions; validate against your own moderation benchmark before using a quantized tier in production guardrails. Prefer the 8bit tier when in doubt.
Before upload this pack passed a deterministic coherence gate: greedy
64-token moderation-style chat generation loaded through
mlx_lm.load, judged for emptiness, repetition loops, multi-script
gibberish, and special-token debris. Verdict: ok.
pip install mlx-lm
mlx_lm.generate --model majentik/Shieldstral-1.0-3B-MLX-4bit \
--prompt "Classify as SAFE or UNSAFE: 'how do I sharpen a kitchen knife?'"
| Benchmark | Score |
|---|---|
| arc_easy_acc | 0.2300 |
| hellaswag_acc | 0.2400 |