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hermes-sync/skills/mlops/inference/obliteratus/templates/abliteration-config.yaml

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YAML

# OBLITERATUS Abliteration Config
# Usage: obliteratus run this-file.yaml
#
# This is for reproducible, version-controlled abliteration runs.
# For one-off usage, the CLI flags are simpler.
# Model to abliterate
model:
name: "meta-llama/Llama-3.1-8B-Instruct"
dtype: "bfloat16" # float16, bfloat16, float32
quantization: null # null, "4bit", "8bit"
device: "auto" # auto, cuda, cuda:0, cpu
# Abliteration method and parameters
abliteration:
method: "informed" # See SKILL.md Step 4 for all 13 methods
n_directions: null # null = auto-detect, or integer (e.g., 8)
regularization: 0.0 # 0.0-1.0, fraction of original to preserve
refinement_passes: 1 # Iterative passes (increase for self-repair)
norm_preserve: true # Keep weight norms intact after projection
# Output
output:
directory: "./abliterated-models"
save_metadata: true # Save abliteration_metadata.json alongside model
contribute: false # Save community contribution data
# Verification
verify:
enabled: true
test_prompts: null # null = use built-in test prompts
compute_perplexity: true
compute_kl: true