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mradermacher/Gemma-4-12b-it-Abliterated-i1-GGUF

mradermacher Gemma 12B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 7,420
  • 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='Carlosian/Gemma-4-12b-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
7K
2K last 30d - stable
Likes
1
Model age
2mo ago
created 2026-07-15
Downloads over time
Now7.7K→from3.9K↑99%
3.7K5.1K6.6K8.1K3.9K on Jul 157.7K on Oct 11JulAugSepOct
Jul 15 → Oct 11 · 53 snapshots · spans 88 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
gemma
Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf gemma gemma4 abliterated uncensored refusal-removal mechanistic-interpretability red-teaming research en base_model:Carlosian/Gemma-4-12b-it-Abliterated

Related

Total size
131 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-07-15 16:27

Files by quantization

Q6_K 1 file 9.11 GB
Gemma-4-12b-it-Abliterated.i1-Q6_K.gguf 9.11 GB d3edc3f5 download
Q5_K 2 files 15.7 GB
Gemma-4-12b-it-Abliterated.i1-Q5_K_M.gguf 7.96 GB fc893813 download
Gemma-4-12b-it-Abliterated.i1-Q5_K_S.gguf 7.77 GB 2c0eec00 download
Q4 2 files 13.6 GB
Gemma-4-12b-it-Abliterated.i1-Q4_1.gguf 7.13 GB e06ab3d1 download
Gemma-4-12b-it-Abliterated.i1-Q4_0.gguf 6.52 GB fd175c7b download
Q4_K 2 files 13.4 GB
Gemma-4-12b-it-Abliterated.i1-Q4_K_M.gguf 6.87 GB aa13c294 download
Gemma-4-12b-it-Abliterated.i1-Q4_K_S.gguf 6.54 GB ef211d91 download
IQ4 2 files 12.7 GB
Gemma-4-12b-it-Abliterated.i1-IQ4_NL.gguf 6.50 GB bd094c98 download
Gemma-4-12b-it-Abliterated.i1-IQ4_XS.gguf 6.18 GB c2f3da5d download
Q3_K 3 files 16.9 GB
Gemma-4-12b-it-Abliterated.i1-Q3_K_L.gguf 6.12 GB 6e93c445 download
Gemma-4-12b-it-Abliterated.i1-Q3_K_M.gguf 5.67 GB c57152d0 download
Gemma-4-12b-it-Abliterated.i1-Q3_K_S.gguf 5.15 GB caf6715e download
IQ3 4 files 19.9 GB
Gemma-4-12b-it-Abliterated.i1-IQ3_M.gguf 5.34 GB cc5d2ba2 download
Gemma-4-12b-it-Abliterated.i1-IQ3_S.gguf 5.15 GB 8849279d download
Gemma-4-12b-it-Abliterated.i1-IQ3_XS.gguf 4.91 GB 1868fb52 download
Gemma-4-12b-it-Abliterated.i1-IQ3_XXS.gguf 4.52 GB 6ac728be download
Q2_K 2 files 8.69 GB
Gemma-4-12b-it-Abliterated.i1-Q2_K.gguf 4.50 GB 7defb967 download
Gemma-4-12b-it-Abliterated.i1-Q2_K_S.gguf 4.19 GB 7d3f7034 download
IQ2 4 files 14.8 GB
Gemma-4-12b-it-Abliterated.i1-IQ2_M.gguf 4.07 GB c5a56ffa download
Gemma-4-12b-it-Abliterated.i1-IQ2_S.gguf 3.80 GB 39440fe3 download
Gemma-4-12b-it-Abliterated.i1-IQ2_XS.gguf 3.62 GB d4bf881c download
Gemma-4-12b-it-Abliterated.i1-IQ2_XXS.gguf 3.32 GB 3e45da10 download
IQ1 2 files 5.76 GB
Gemma-4-12b-it-Abliterated.i1-IQ1_M.gguf 2.98 GB bfb9855a download
Gemma-4-12b-it-Abliterated.i1-IQ1_S.gguf 2.78 GB fd508780 download
Auxiliary files 3 files 7.14 MB
Gemma-4-12b-it-Abliterated.imatrix.gguf 7.13 MB 3c1e0de2 download
README.md 6.66 KB d508920c download
.gitattributes 3.37 KB ff1bc948 download

README current version from Hugging Face


base_model: Carlosian/Gemma-4-12b-it-Abliterated
language:

  • en
    library_name: transformers
    license: gemma
    license_link: https://ai.google.dev/gemma/terms
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • gemma
  • gemma4
  • abliterated
  • uncensored
  • refusal-removal
  • mechanistic-interpretability
  • red-teaming
  • research

About

weighted/imatrix quants of https://huggingface.co/Carlosian/Gemma-4-12b-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/Gemma-4-12b-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 3 versions

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

  1. 2026-07-15auto-patch README.md1e9fa6a6.7 KB
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  2. 2026-07-15auto-patch README.md7f357952.7 KB
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  3. 2026-07-15uploaded from nico1537f5fa483 B
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