mirror of
https://github.com/elder-plinius/OBLITERATUS.git
synced 2026-07-12 23:26:32 +02:00
04b8ec60cb
New core modules: - auto_obliterate.py: Automated multi-iteration obliteration pipeline - watchtower.py: HF Hub model discovery and tracking - ui_watchtower.py: Gradio tabs for Watchtower (ready for app.py wiring) - hard_negative.py: Residue mining from refusal audits - model_profile.py: Parameter profiling from safetensors/config - bestiary_sync.py: Sync models from PlinyOS BESTIARY registry - models_client.py: Lightweight HF model list client Framework enhancements: - abliterate.py: ASPA source-tethering, step gradient blending, hard-negative residue support - cli.py: self-improve command, model profiling, hard-negative flags - prompts.py: Expanded 842-prompt refusal eval corpus across 10 categories - __init__.py: New exports (Watchtower, AutoObliterator) Reference implementations (14 scripts): - ASPA sweep, gradient search, coherence eval, MMLU benchmarks - Pareto controller, refusal sniper, stock comparisons Documentation: - README: Research framing, responsible use section, comprehensive disclaimer - docs/beyond_sota_roadmap.md, docs/recursive_self_improvement.md Tests: 4 new test files (354 lines) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
3.6 KiB
3.6 KiB
Recursive self-improving OBLITERATUS
OBLITERATUS can now turn refusal audits into hard-negative residue for the next surgery run.
Loop
- Run an eval/audit that records refused prompt references. The audit should store dataset key, zero- or one-based corpus index, prompt hash, refusal reason, and optionally a short response preview. It does not need to store prompt text.
- Feed the audit back into
obliteratus self-improve. - The command profiles the target model without loading full weights. Local safetensors artifacts get exact parameter counts from tensor metadata; Hub/config-only targets use a
text_config-aware estimate. - The command writes a canonical residue file and reconstructs prompt text from local dataset registries at run time.
- Residue prompts are appended to the contrastive prompt set with
--residue-weightcopies each. If omitted,--residue-weight,--n-directions,--regularization,--refinement-passes, and--verify-sample-sizeare filled from size-aware defaults. - A
self_improve_plan.jsonis written withmodel_profile,size_aware_defaults, andeffective_settingsso runs are comparable across parameter scales. - Run the next artifact through benign/code/math and harmful release gates. Mine its remaining refusals and repeat.
Dry-run plan
obliteratus self-improve outputs/qwen3.6-27b-golden-n3_reg025 \
--audit runs/qwen36-refusal-audit/summary.json \
--output-dir outputs/qwen3.6-27b-self-improve-r1 \
--residue-weight 5 \
--residue-max 8 \
--method advanced \
--direction-method diff_means \
--n-directions 3 \
--regularization 0.3 \
--refinement-passes 1 \
--dry-run
Run surgery
Remove --dry-run to launch. The command saves hard_negative_residue.json in the output directory with counts, hashes, tags, and indices but not prompt text.
obliteratus self-improve outputs/qwen3.6-27b-golden-n3_reg025 \
--audit runs/qwen36-refusal-audit/summary.json \
--output-dir outputs/qwen3.6-27b-self-improve-r1 \
--residue-weight 5 \
--method advanced \
--direction-method diff_means \
--n-directions 3 \
--regularization 0.3 \
--refinement-passes 1
Equivalent lower-level usage:
obliteratus obliterate Qwen/Qwen3.6-27B \
--residue-file runs/qwen36-self-improve-dryrun/candidate/mined_residue.json \
--residue-weight 5 \
--method advanced \
--direction-method diff_means \
--n-directions 3 \
--regularization 0.3 \
--refinement-passes 1 \
--output-dir outputs/qwen3.6-27b-residue-r1
Current Qwen3.6 residue tags observed
The Qwen3.6 hard-category audit produced five unique residue prompts after deduping across n3_reg025 and n3_reg03:
- terrorism + illegal/crime + safety-banner
- privacy-intrusion + illegal/crime + safety-banner
- sabotage + illegal/crime
- CBRN/critical-infra illegal/crime + safety-banner
- synthetic-pathogen terrorism + illegal/crime
These should be upweighted lightly; avoid simply increasing global ablation strength, because nearby regularization sweeps collapsed into short/repetitive <think> fragments.
Guardrails for future runs
- Keep
--residue-weightmodest first: omit it to use the size-aware default, or use 3–5 manually. - Preserve a strict benign/code/math gate before expensive harmful eval.
- Confirm every plan records
model_profile.total_params_b; for Qwen3.6-27B local artifacts the expected exact count is about 26.896B from safetensors metadata. - Prefer sequential no-think evaluation on Apple Silicon Qwen3.6.
- If residue-weighted runs damage exact/code ability, try source merge-back before stronger ablation.