license: apache-2.0
base_model: ibm-granite/granite-4.2-8b
tags:
- granite
- uncensored
- abliterated
- heretic
granite-4.2-8b-decensored
Uncensored (abliterated) version of
ibm-granite/granite-4.2-8b,
produced with heretic v2.0.0.dev0.
Ready-to-use GGUF quantizations:
qcokvd1/granite-4.2-8b-decensored-GGUF
Method
Directional ablation ("abliteration") of the refusal direction in attention
out-projection and MLP down-projection matrices, applied as low-rank LoRA
corrections and merged back into the original BF16 weights. Abliteration
parameters were tuned by Optuna (TPE) over 200 trials, co-minimizing the
refusal keyword rate and KL divergence from the original model.
The optimization itself ran on-the-fly quantized to NF4 (bitsandbytes); the
4-bit working precision only affects how the correction was computed — the
exported weights are derived from the original BF16 model.
Results
| Metric | Original | Decensored |
|---|---|---|
| Refusal keyword rate (mlabonne/harmful_behaviors, 100 prompts) | 97/100 | 33/100 |
| KL divergence vs original | — | 0.0655 |
Selected trial #11 (lowest refusal rate on the Pareto front), parameters:direction_index = 29.89, attn.o_proj: max_weight 1.28 @ layer 31.07, min_weight 0.93, distance 9.46, mlp.down_proj: max_weight 1.46 @ layer 23.56, min_weight 1.43, distance 9.86.
Quality spot-check (code / math / SQL / logic, 9 prompts, greedy): answers match
the original model, <think>-reasoning intact — see evaluation/.
Raw Optuna study journal for resuming/extending the optimization:heretic-study.jsonl (rename to your model-path-derived name in
heretic's checkpoints/ directory to resume).
Reproduction configuration
model = "<local path to ibm-granite/granite-4.2-8b>"
quantization = "bnb_4bit"
export_strategy = "merge"
trial_index = 0 # lowest refusal on the Pareto front
batch_size = 0 # auto (chosen: 128 on RTX 5060 Ti 16GB)
n_trials = 200
Hardware reference: RTX 5060 Ti 16 GB, ~7.5 h wall clock including export.
Disclaimer
Safety guardrails of the base model have been removed. You are solely
responsible for how you use and deploy this model. The model may produce
inaccurate, biased or unsafe content.
Base model © IBM, released under Apache-2.0; this redistribution complies with
the license and attributes the original authors.