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mradermacher/Gemma4-12B-IT-Abliterated-i1-GGUF

mradermacher Gemma 12B GGUF multimodal second-order 131K ctx
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Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 14,553
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='DuoNeural/Gemma4-12B-IT-Abliterated' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
15K
2K last 30d - stable
Likes
2
Model age
4mo ago
created 2026-06-06
Downloads over time
Now15K→from4.3K↑252%
3.7K7.8K12K16.1K4.3K on Jun 1015K on Oct 12JunJulAugSepOct
Jun 10 → Oct 12 · 58 snapshots · spans 124 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 · 3K 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
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf abliteration uncensored gemma gemma4 multimodal DuoNeural refusal-removal orthogonal-projection en base_model:DuoNeural/Gemma4-12B-IT-Abliterated

Related

Total size
131 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-07-03 11:10

Files by quantization

Q6_K 1 file 9.11 GB
Gemma4-12B-IT-Abliterated.i1-Q6_K.gguf 9.11 GB e584ea27 download
Q5_K 2 files 15.7 GB
Gemma4-12B-IT-Abliterated.i1-Q5_K_M.gguf 7.96 GB 250a73ce download
Gemma4-12B-IT-Abliterated.i1-Q5_K_S.gguf 7.77 GB b193a57e download
Q4 2 files 13.6 GB
Gemma4-12B-IT-Abliterated.i1-Q4_1.gguf 7.13 GB dc5164c2 download
Gemma4-12B-IT-Abliterated.i1-Q4_0.gguf 6.52 GB 22bce330 download
Q4_K 2 files 13.4 GB
Gemma4-12B-IT-Abliterated.i1-Q4_K_M.gguf 6.87 GB 18d17dd5 download
Gemma4-12B-IT-Abliterated.i1-Q4_K_S.gguf 6.54 GB 89afc57a download
IQ4 2 files 12.7 GB
Gemma4-12B-IT-Abliterated.i1-IQ4_NL.gguf 6.50 GB e1e2fec8 download
Gemma4-12B-IT-Abliterated.i1-IQ4_XS.gguf 6.18 GB fd65b94b download
Q3_K 3 files 16.9 GB
Gemma4-12B-IT-Abliterated.i1-Q3_K_L.gguf 6.12 GB 8e5e5a6f download
Gemma4-12B-IT-Abliterated.i1-Q3_K_M.gguf 5.67 GB 4c9de8da download
Gemma4-12B-IT-Abliterated.i1-Q3_K_S.gguf 5.15 GB aafa5632 download
IQ3 4 files 19.9 GB
Gemma4-12B-IT-Abliterated.i1-IQ3_M.gguf 5.34 GB e1a75367 download
Gemma4-12B-IT-Abliterated.i1-IQ3_S.gguf 5.15 GB d94545f4 download
Gemma4-12B-IT-Abliterated.i1-IQ3_XS.gguf 4.91 GB b2572d81 download
Gemma4-12B-IT-Abliterated.i1-IQ3_XXS.gguf 4.52 GB 4524b697 download
Q2_K 2 files 8.69 GB
Gemma4-12B-IT-Abliterated.i1-Q2_K.gguf 4.50 GB 6faebd4c download
Gemma4-12B-IT-Abliterated.i1-Q2_K_S.gguf 4.19 GB 0d41dbe2 download
IQ2 4 files 14.8 GB
Gemma4-12B-IT-Abliterated.i1-IQ2_M.gguf 4.07 GB 6b62eb47 download
Gemma4-12B-IT-Abliterated.i1-IQ2_S.gguf 3.80 GB cbb8f937 download
Gemma4-12B-IT-Abliterated.i1-IQ2_XS.gguf 3.62 GB 51adf041 download
Gemma4-12B-IT-Abliterated.i1-IQ2_XXS.gguf 3.32 GB 197b0fc7 download
IQ1 2 files 5.76 GB
Gemma4-12B-IT-Abliterated.i1-IQ1_M.gguf 2.98 GB a6368f27 download
Gemma4-12B-IT-Abliterated.i1-IQ1_S.gguf 2.78 GB d73c7ace download
Auxiliary files 3 files 7.14 MB
Gemma4-12B-IT-Abliterated.imatrix.gguf 7.13 MB 45260af4 download
README.md 6.55 KB 162b388d download
.gitattributes 3.35 KB 06b7e6f0 download

README current version from Hugging Face


base_model: DuoNeural/Gemma4-12B-IT-Abliterated
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliteration
  • uncensored
  • gemma
  • gemma4
  • multimodal
  • DuoNeural
  • refusal-removal
  • orthogonal-projection

About

weighted/imatrix quants of https://huggingface.co/DuoNeural/Gemma4-12B-IT-Abliterated

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

static quants are available at https://huggingface.co/mradermacher/Gemma4-12B-IT-Abliterated-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

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 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 3.1 for the desperate
GGUF i1-IQ1_M 3.3 mostly desperate
GGUF i1-IQ2_XXS 3.7
GGUF i1-IQ2_XS 4.0
GGUF i1-IQ2_S 4.2
GGUF i1-IQ2_M 4.5
GGUF i1-Q2_K_S 4.6 very low quality
GGUF i1-Q2_K 4.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 4.9 lower quality
GGUF i1-IQ3_XS 5.4
GGUF i1-IQ3_S 5.6 beats Q3_K*
GGUF i1-Q3_K_S 5.6 IQ3_XS probably better
GGUF i1-IQ3_M 5.8
GGUF i1-Q3_K_M 6.2 IQ3_S probably better
GGUF i1-Q3_K_L 6.7 IQ3_M probably better
GGUF i1-IQ4_XS 6.7
GGUF i1-IQ4_NL 7.1 prefer IQ4_XS
GGUF i1-Q4_0 7.1 fast, low quality
GGUF i1-Q4_K_S 7.1 optimal size/speed/quality
GGUF i1-Q4_K_M 7.5 fast, recommended
GGUF i1-Q4_1 7.8
GGUF i1-Q5_K_S 8.4
GGUF i1-Q5_K_M 8.6
GGUF i1-Q6_K 9.9 practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

README history 5 versions

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

  1. 2026-07-03auto-patch README.md52c23686.6 KB
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  2. 2026-06-30auto-patch README.md0ce42c16.4 KB
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  3. 2026-06-06auto-patch README.md6dd6b7a6.6 KB
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  4. 2026-06-06auto-patch README.md1ef6a593.1 KB
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  5. 2026-06-06uploaded from nico1c72a3d4482 B
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