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alexokita/Darkhn-M3.2-36B-Animus-V12.0-Heretic-Uncensored-i1-GGUF

alexokita Mistral 36B GGUF second-order 131K ctx
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
5K
205 last 30d - cooling
Likes
1
Model age
2mo ago
created 2026-08-30
Downloads over time
Now5.4K→from0↑0%
02K3.9K5.9K0 on Aug 305.4K on Oct 30AugSepOct
Aug 30 → Oct 30 · 62 snapshots · spans 61 days

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Languages
en
Tags
transformers gguf imatrix heretic uncensored mistral finetune roleplay chat nsfw not-for-all-audiences text-generation
Total size
0 B
Files
2
Quantizations
1
Registered
2026-08-30 08:03
Last updated on HF
2026-08-30 10:04

Files by quantization

Auxiliary files 2 files 5.26 KB
README.md 3.78 KB 6455e31b download
.gitattributes 1.48 KB a6344aac download

README current version from Hugging Face


base_model: Silicone-Moss/Darkhn-M3.2-36B-Animus-V12.0-Heretic-Uncensored
base_model_relation: quantized
language:

  • en
    library_name: transformers
    license: apache-2.0
    pipeline_tag: text-generation
    quantized_by: alexokita
    tags:
  • gguf
  • imatrix
  • heretic
  • uncensored
  • mistral
  • finetune
  • roleplay
  • chat
  • nsfw
  • not-for-all-audiences

About

weighted/imatrix quants of https://huggingface.co/Silicone-Moss/Darkhn-M3.2-36B-Animus-V12.0-Heretic-Uncensored

Dense Mistral 36B (Heretic trial 177: 8/100 refusals, KL 0.0200). Text-only — no mmproj.

These are i1 (importance-matrix) GGUFs in the mradermacher naming style, converted with llama.cpp on an NVIDIA GB10. Calibration: froggeric/imatrix groups_merged.txt (llama-imatrix -c 512).

Original weights: Darkhn/M3.2-36B-Animus-V12.0. Abliteration: p-e-w/heretic.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF imatrix 0.02 imatrix file (for creating your own quants)
GGUF i1-IQ3_M 15.5 smallest in this pack
GGUF i1-IQ4_XS 18.7
GGUF i1-Q4_K_S 19.8 optimal size/speed/quality
GGUF i1-Q4_K_M 21.0 fast, recommended
GGUF i1-Q5_K_S 23.9
GGUF i1-Q5_K_M 24.6
GGUF i1-Q6_K 28.5 practically like static Q6_K
GGUF i1-Q8_0 36.9 high quality; imatrix unused

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

Thanks

Source weights by Silicone-Moss / Darkhn. Heretic by p-e-w. Conversion with llama.cpp.

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-08-30Add mradermacher-style model carde79c84c3.8 KB
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