license: other
task_categories:

• text-generation
  language:
• en
  tags:
• safety
• refusal
• abliteration
• red-teaming
  pretty_name: Heretic Completions
  configs:
• config_name: gemma-abliterated
  data_files: data/gemma-abliterated.jsonl
• config_name: gpt-oss-heretic
  data_files: data/gpt-oss-heretic.jsonl

Heretic Completions

Model completions used as SFT targets for a refusal-abliteration LoRA study.
Each row pairs a prompt from a red-teaming / over-refusal benchmark with a
completion from a refusal-removed ("heretic" / abliterated) model.

Safety notice. This is a private research dataset. Many completions
comply with harmful or dual-use requests by design, so the refusal signal
can be measured and abliteration studied. Do not redistribute or use outside
authorized safety research.

Configs

gemma-abliterated covers every prompt in the source set (all splits).
gpt-oss-heretic covers only the training-split harmful sources
(or_bench_hard, do_not_answer, advbench, harmbench,
malicious_instruct); it was generated at temperature=1.0,
max_tokens=4096.

Fields

Common: id, source, split, prompt, completion, and label where the
source provides one (xstest safe / unsafe).

gpt-oss-heretic adds: reasoning (the model's analysis-channel trace),
finish_reason, completion_tokens, reasoning_tokens, and refused (the
shared repo refusal regex applied to completion).

Caveats for gpt-oss-heretic

• 172 rows are flagged refused=true by the refusal regex. Many are
  capability disclaimers ("I'm not able to look up personal data"), not safety
  refusals, but the flag is not hand-verified. Filter on refused before using
  as compliant SFT targets.
• 175 rows have finish_reason="length" (truncated at 4096 tokens). Their
  completion may be cut off mid-answer.

Provenance

Generated by the sft_lora_pipeline package (scripts/gen_completions.py).
Prompt metadata joined from the pipeline's data/raw/prompts.jsonl. Completions
inherit their base models' licenses (Gemma and gpt-oss terms respectively).