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How to confirm the ablation hooks fire before evaluating with Orca Bonsai 27B Uncensored

Run the self-check to confirm 129 residual writers are wrapped and the refusal component drops.

  • Research
  • Intermediate
  • 1 hour
  • From the README
  • Any agent

Who it is forAn ML engineer about to run evaluations on this pack who needs to know the intervention is actually applied.

The problemIf the residual writers are not wrapped correctly, results look like the unmodified model and the ablation silently does nothing.

The outcomeA confirmed count of 129 wrapped residual writers and a near-zero remaining refusal-direction component after intervention.

What you need first

  • An Apple Silicon Mac with MLX, as the README describes
  • Python with pip to install requirements.txt
  • The original prism-ml/Ternary-Bonsai-2-27B-mlx-2bit pack, which you supply yourself

Steps

  1. pip install -r requirements.txt
  2. python scripts/selfcheck.py --pack /path/to/Ternary-Bonsai-2-27B-mlx-2bit (inferred, check the README)
  3. Check that the output reports 129 residual writers and that the remaining component is approximately 1e-6 of the residual norm.
  4. python scripts/test_ablation.py
  5. Record the results and do not run evaluations if the count or the residual value is wrong.

Prompt for your agent

In the repo Continuum-AI-Corp/OrcaBonsai-27B-Uncensored, run python scripts/selfcheck.py with --pack set to <pack-path>. Expected output: 129 residual writers detected and a remaining refusal-direction component near 1e-6 of the residual norm. Verify both numbers before reporting success.

Caveat. The README says the packed quantized matmul has no CUDA implementation, so the 27B pack path targets Apple Silicon, while scripts/test_ablation.py is model-free and does not need the pack.

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