Yes... fully uncensored AND fine tuned lightly.

Freedom and brainpower.

Trained on different Heretic base, with different KLD/Refusals.

Model fine tune was used to finalize and "firm up" Heretic / uncensored changes.

The goal here was light, minor fixes rather than full / heavy fine tune.

That being said, the tuning still raised critical metrics.

This is Version 2, using "trohrbaugh" Heretic, which has a lower refusal rate, and tuning bumped up the metrics a bit more too.

This has also positively impacted "NEO-Coder Di-Matrix" (dual imatrix) GGUF quants as well (vs heretic/non heretic too).

https://huggingface.co/DavidAU/Qwen3.6-27B-Heretic-Uncensored-FINETUNE-NEO-CODE-Di-IMatrix-MAX-GGUF

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IN HOUSE BENCHMARKS [by Nightmedia]:

         arc-c arc/e boolq hswag obkqa piqa  wino

Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking
mxfp8    0.673,0.846,0.905... [instruct mode]

Qwen3.6-27B-Heretic-Uncensored-Finetune-Thinking
mxfp8    0.669,0.835,0.906,...   [instruct mode]

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BASE UNTUNED MODEL:

Qwen3.6-27B HERETIC (by llmfan46) [instruct mode]
mxfp8    0.644,0.788,0.902,...

Qwen3.6-27B (by Qwen) [instruct mode]
mxfp8    0.647,0.803,0.910,0.773,0.450,0.806,0.742

NOTE: Instruct mode will often test higher than "thinking" mode due to token usage in thinking and context limits.

Heretic Stats:

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Metric 			This model 		Original model (Qwen/Qwen3.6-27B)
KL divergence 	0.0469 			0 (by definition)
Refusals 		4/100 			99/100

A KLD of .3 or lower is great, lower than this excellent.

KLD measures HERETIC vs Original model performance:

IE: How closely the Heretic version matchs in generation / token selection vs org model.

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Q4KS, non imatrix, temp:1, rep pen: 1 [off]

There may be some loss of formatting from copy/paste.

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