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karlsencoin/Karlsen-Gemma-4-26B-A4B-abliterated-GGUF

karlsencoin Gemma 26B GGUF MoE second-order
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Response includes
  • classification m8
  • files 3
  • author_summary 2 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
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
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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Model age
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created 2026-10-28

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Metadata

License
apache-2.0
Languages
en
Quantizations
Q5_K
Tags
transformers gguf abliterated uncensored en base_model:huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated base_model:quantized:huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated license:apache-2.0 endpoints_compatible region:us imatrix conversational

Related

Total size
17.8 GB
Files
3
Quantizations
2
Registered
2026-10-28 12:01
Last updated on HF
2026-10-28 11:58

Files by quantization

Q5_K 1 file 17.8 GB
Huihui-gemma-4-26B-A4B-it-abliterated.i1-Q5_K_M.gguf 17.8 GB 345fb668 download
Auxiliary files 2 files 10.6 KB
README.md 7.00 KB 2db4dbae download
.gitattributes 3.56 KB 5d07f183 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-gemma-4-26B-A4B-it-abliterated
language:


About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-gemma-4-26B-A4B-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/Huihui-gemma-4-26B-A4B-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 0.2 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 8.4 for the desperate
GGUF i1-IQ1_M 8.8 mostly desperate
GGUF i1-IQ2_XXS 9.4
GGUF i1-IQ2_XS 9.9
GGUF i1-IQ2_S 10.0
GGUF i1-IQ2_M 10.5
GGUF i1-Q2_K 10.7 IQ3_XXS probably better
GGUF i1-Q2_K_S 10.7 very low quality
GGUF i1-IQ3_XXS 11.4 lower quality
GGUF i1-IQ3_XS 11.7
GGUF i1-IQ3_S 12.3 beats Q3_K*
GGUF i1-Q3_K_S 12.3 IQ3_XS probably better
GGUF i1-IQ3_M 12.5
GGUF i1-Q3_K_M 13.4 IQ3_S probably better
GGUF i1-Q3_K_L 13.9 IQ3_M probably better
GGUF i1-IQ4_XS 14.0
GGUF i1-Q4_0 14.6 fast, low quality
GGUF i1-Q4_K_S 15.6 optimal size/speed/quality
GGUF i1-Q4_1 16.1
GGUF i1-Q4_K_M 16.9 fast, recommended
GGUF i1-Q5_K_S 18.1
GGUF i1-Q5_K_M 19.2
GGUF i1-Q6_K 22.7 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.

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