Results
Table with columns: Refusals, KL divergence | Refusals | KL divergence |
|---|
| Original Qwen3.5-0.8B | 98/100 | 0 (by definition) |
| This model | 15/100 | 0.0714 |
Measured by Heretic on the test[:100] splits of mlabonne/harmful_behaviors (refusals) and
mlabonne/harmless_alpaca (KL divergence, the drift in ordinary behaviour), with Heretic's default system prompt and
refusal markers. The numbers come from an independent re-evaluation of the final exported weights (evaluate_model).
Built on dalatexcoder's findings, and why it stops at 15/100
The search started from dalatexcoder's four published Qwen3.5-0.8B ARA parameter sets. The strongest of them gives
1/100 refusals with this toolchain (at KL 0.0993), but that model's reasoning broke down: in thinking mode it finished
and correctly answered only 10 of 40 arithmetic and word problems, against 26 of 40 for the original. At 0.8B, every
setting found that pushes refusals much lower costs reasoning like that. This release is the strongest setting that
leaves reasoning intact (27 of 40), at 15/100 refusals. If you need fewer refusals and can accept weaker reasoning,
dalatexcoder/Qwen3.5-0.8B-heretic-ara-high-kld
is the stronger edit.
What this release adds is a complete checkpoint: save_pretrained drops Qwen3.5's 15 multi-token-prediction tensors
and rounds the 36 float32 Gated DeltaNet parameters (linear_attn.A_log, linear_attn.norm.weight) down to bf16.
Both were restored from the original here (ARA never touches either), so all 488 tensors match the original in name,
shape and dtype. The MTP weights live in model-auxiliary.safetensors, listed in the index.
Parameters
ARA, full weight, on attn.o_proj and mlp.down_proj:
Table with columns: Parameter, Value| Parameter | Value |
|---|
| start_layer_index | 11 |
| end_layer_index | 17 |
| preserve_good_behavior_weight | 0.8645 |
| steer_bad_behavior_weight | 0.001 |
| overcorrect_relative_weight | 0.202 |
| neighbor_count | 14 |
Calibration used 400 harmless and 400 harmful prompts (train[:400]).
Checked
- Ordinary prompts (facts, a haiku, a two-sentence technical explanation): correct and fluent.
- Thinking-mode reasoning, 4 arithmetic and word problems x 10 seeds with Qwen's recommended sampling (vLLM): 27/40
finished and answered correctly, against 26/40 for the original. At 0.8B, non-thinking arithmetic is unreliable in
both this model and the original; turn thinking on for anything that needs reasoning.
- Vision: given an image of a red circle and a blue square, it describes exactly that.
A merge of upstream Heretic's master and its ara branch (ARA with master's scorers and thinking-model handling),
Heretic upstream 3521f86 + ARA c91d690, transformers 5.17.0, torch 2.11.0+cu130, one RTX PRO 6000.
Use
Exactly like the original, with transformers, vLLM or SGLang. Thinking mode is on by default and can be turned off
per request (enable_thinking=False).
Reduced safety guardrails by design. You are responsible for what you do with it.
The family