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mradermacher/gemma-4-12B-it-heretic_decensored-GGUF

mradermacher Gemma 12B GGUF second-order
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Response includes
  • classification m3
  • files 15
  • author_summary 3324 models
  • readme_text full
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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 · 30-day
2K
↑ 327% in 90 days
Likes
4
Model age
3mo ago
created 2026-06-18
Downloads over time
Now5.3K→from1.2K↑327%
1K2.6K4.2K5.7K1.2K on Jun 175.3K on Oct 11JunJulAugSepOct
Jun 17 → Oct 11 · 57 snapshots · spans 116 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 4K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
apache-2.0
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf text-generation-inference pytorch decensored abliterated unfiltered unredacted heretic bf16 en base_model:prithivMLmods/gemma-4-12B-it-heretic_decensored

Related

Total size
77.7 GB
Files
15
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-10-09 18:03

Files by quantization

Q8_0 2 files 11.9 GB
gemma-4-12B-it-heretic_decensored.Q8_0.gguf 11.8 GB 4cc7b568 download
gemma-4-12B-it-heretic_decensored.mmproj-Q8_0.gguf 152 MB 37be1873 download
Q6_K 1 file 9.11 GB
gemma-4-12B-it-heretic_decensored.Q6_K.gguf 9.11 GB 4bcdb4f4 download
Q5_K 2 files 15.7 GB
gemma-4-12B-it-heretic_decensored.Q5_K_M.gguf 7.96 GB 735fad3a download
gemma-4-12B-it-heretic_decensored.Q5_K_S.gguf 7.77 GB 765ef9c9 download
Q4_K 2 files 13.4 GB
gemma-4-12B-it-heretic_decensored.Q4_K_M.gguf 6.87 GB 5574008b download
gemma-4-12B-it-heretic_decensored.Q4_K_S.gguf 6.54 GB a81fbf1f download
IQ4 1 file 6.23 GB
gemma-4-12B-it-heretic_decensored.IQ4_XS.gguf 6.23 GB a8c9a448 download
Q3_K 3 files 16.9 GB
gemma-4-12B-it-heretic_decensored.Q3_K_L.gguf 6.12 GB 61a04ef8 download
gemma-4-12B-it-heretic_decensored.Q3_K_M.gguf 5.67 GB de7d9bae download
gemma-4-12B-it-heretic_decensored.Q3_K_S.gguf 5.15 GB c1bb62e8 download
Q2_K 1 file 4.50 GB
gemma-4-12B-it-heretic_decensored.Q2_K.gguf 4.50 GB 5791910e download
F16 1 file 116 MB
gemma-4-12B-it-heretic_decensored.mmproj-f16.gguf 116 MB d6124eea download
Auxiliary files 2 files 6.76 KB
README.md 4.23 KB a102b238 download
.gitattributes 2.53 KB c3a622da download

README current version from Hugging Face


base_model: prithivMLmods/gemma-4-12B-it-heretic_decensored
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • text-generation-inference
  • pytorch
  • decensored
  • abliterated
  • unfiltered
  • unredacted
  • heretic
  • bf16

About

static quants of https://huggingface.co/prithivMLmods/gemma-4-12B-it-heretic_decensored

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/gemma-4-12B-it-heretic_decensored-i1-GGUF

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 mmproj-f16 0.2 multi-modal supplement
GGUF mmproj-Q8_0 0.3 multi-modal supplement
GGUF Q2_K 4.9
GGUF Q3_K_S 5.6
GGUF Q3_K_M 6.2 lower quality
GGUF Q3_K_L 6.7
GGUF IQ4_XS 6.8
GGUF Q4_K_S 7.1 fast, recommended
GGUF Q4_K_M 7.5 fast, recommended
GGUF Q5_K_S 8.4
GGUF Q5_K_M 8.6
GGUF Q6_K 9.9 very good quality
GGUF Q8_0 12.8 fast, best quality

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

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

README history 5 versions

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

  1. 2026-10-09auto-patch README.md968c53f4.5 KB
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  2. 2026-06-18auto-patch README.mda0bc01e4.2 KB
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  3. 2026-06-18auto-patch README.mdba4433f4.3 KB
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  4. 2026-06-18auto-patch README.md0848a723.9 KB
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  5. 2026-06-18uploaded from nico1508dc18390 B
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