mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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24f816b6a3
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):
- brain/ LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
dispatch, A51 channels, and the OSINT cluster
- knowledge/ LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
MITRE ATT&CK data
- reference/ defensive threat-reference (C3, shhbruh doc) + AdaYaml parser
License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.
Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.
https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
42 lines
1.2 KiB
YAML
42 lines
1.2 KiB
YAML
# OBLITERATUS Batch Abliteration Config
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# Abliterate multiple models with the same method for comparison.
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#
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# Run each one sequentially:
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# for model in models; do obliteratus obliterate $model --method informed; done
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#
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# Or use this as a reference for which models to process.
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# Common settings
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defaults:
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method: "informed"
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quantization: "4bit"
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output_dir: "./abliterated-models"
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# Models to process (grouped by compute tier)
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models:
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# Small (4-8 GB VRAM)
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small:
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- "Qwen/Qwen2.5-1.5B-Instruct"
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- "microsoft/Phi-3.5-mini-instruct"
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- "meta-llama/Llama-3.2-3B-Instruct"
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# Medium (8-16 GB VRAM)
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medium:
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- "meta-llama/Llama-3.1-8B-Instruct"
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- "mistralai/Mistral-7B-Instruct-v0.3"
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- "google/gemma-2-9b-it"
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- "Qwen/Qwen2.5-7B-Instruct"
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# Large (24 GB VRAM, 4-bit quantization)
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large:
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- "Qwen/Qwen2.5-14B-Instruct"
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- "Qwen/Qwen3-32B"
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- "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
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# Per-model method overrides (optional)
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overrides:
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"deepseek-ai/DeepSeek-R1-Distill-Qwen-32B":
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method: "surgical" # CoT-aware for reasoning models
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"mistralai/Mixtral-8x7B-Instruct-v0.1":
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method: "nuclear" # Expert-granular for MoE models
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