1pip install -U mlx-vlm
2python -m mlx_vlm generate --model divinetribe/Nemotron-3-Nano-Omni-30B-Abliterated-MM-8bit \
3 --image your_image.jpg --prompt "Describe this image."
Needs a recent
mlx-vlm (0.6.12+) with Omni support. Runtime reference:
https://github.com/nicedreamzapp/nemotron-omni-mlx
Directional ablation (Arditi et al.). The refusal direction on this model is spread
across two blocks (16 and 31), not one — a single-layer ablation leaves it refusing.
Both directions are Gram-Schmidt'd and orthogonalized out of every residual-writing
projection: mamba out_proj, attention o_proj, MoE routed-expert fc2, shared-expert
down_proj, plus the token embeddings.
Safety alignment has been removed. You are responsible for what you generate.
This model is one of the fighters in
Claude Code Local (3.2k★), which runs Claude Code 100% on-device on Apple Silicon through an MLX-native Anthropic-API server. Not sure which local model to run as an agent? Check the
Agent-12 local agent leaderboard: real agent tasks, judged by the filesystem, same hardware for every row.
Built by
Matt Macosko in Arcata, CA. Open to work on local-AI and Apple Silicon inference:
matt@ineedhemp.com.