← back to catalog · registered 2026-08-22 13:56

mradermacher/gemma-4-E4B-it-abliterated-i1-GGUF

mradermacher Gemma GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 27
  • hub_downloads_all_time 12,902
  • 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='WWTCyberLab/gemma-4-E4B-it-abliterated' (base has 'abliterated' marker, assume M1 default)
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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
13K
2K last 30d - stable
Likes
2
Model age
6mo ago
created 2026-04-10
Downloads over time
Now13.5K→from4.3K↑216%
3.8K7.3K10.9K14.4K4.3K on Apr 1513.5K on Oct 12AprMayJunJulAugSepOct
Apr 15 → Oct 12 · 68 snapshots · spans 180 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 · 2K 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 abliteration safety-research alignment gemma4 en base_model:WWTCyberLab/gemma-4-E4B-it-abliterated base_model:quantized:WWTCyberLab/gemma-4-E4B-it-abliterated license:gemma endpoints_compatible region:us

Related

Total size
104 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-07-27 15:05

Files by quantization

Q6_K 1 file 5.79 GB
gemma-4-E4B-it-abliterated.i1-Q6_K.gguf 5.79 GB 89e1fd8b download
Q5_K 2 files 10.7 GB
gemma-4-E4B-it-abliterated.i1-Q5_K_M.gguf 5.37 GB 235ef8ec download
gemma-4-E4B-it-abliterated.i1-Q5_K_S.gguf 5.30 GB 600f6d76 download
Q4 2 files 9.90 GB
gemma-4-E4B-it-abliterated.i1-Q4_1.gguf 5.06 GB c66d3f27 download
gemma-4-E4B-it-abliterated.i1-Q4_0.gguf 4.84 GB 6bdae1af download
Q4_K 2 files 9.81 GB
gemma-4-E4B-it-abliterated.i1-Q4_K_M.gguf 4.97 GB 99b0c043 download
gemma-4-E4B-it-abliterated.i1-Q4_K_S.gguf 4.85 GB 46950591 download
IQ4 2 files 9.56 GB
gemma-4-E4B-it-abliterated.i1-IQ4_NL.gguf 4.84 GB 93612e37 download
gemma-4-E4B-it-abliterated.i1-IQ4_XS.gguf 4.72 GB d9887e42 download
Q3_K 3 files 13.5 GB
gemma-4-E4B-it-abliterated.i1-Q3_K_L.gguf 4.68 GB 304727ae download
gemma-4-E4B-it-abliterated.i1-Q3_K_M.gguf 4.52 GB ec7fad44 download
gemma-4-E4B-it-abliterated.i1-Q3_K_S.gguf 4.33 GB 8ed046f7 download
IQ3 4 files 16.7 GB
gemma-4-E4B-it-abliterated.i1-IQ3_M.gguf 4.39 GB 3921ee88 download
gemma-4-E4B-it-abliterated.i1-IQ3_S.gguf 4.34 GB 4513e4f6 download
gemma-4-E4B-it-abliterated.i1-IQ3_XS.gguf 4.23 GB 3629fad3 download
gemma-4-E4B-it-abliterated.i1-IQ3_XXS.gguf 3.71 GB 7ded8f33 download
Q2_K 2 files 8.08 GB
gemma-4-E4B-it-abliterated.i1-Q2_K.gguf 4.10 GB 553e379b download
gemma-4-E4B-it-abliterated.i1-Q2_K_S.gguf 3.98 GB 99cbbd00 download
IQ2 4 files 13.6 GB
gemma-4-E4B-it-abliterated.i1-IQ2_M.gguf 3.53 GB e356a73e download
gemma-4-E4B-it-abliterated.i1-IQ2_S.gguf 3.42 GB b55780e9 download
gemma-4-E4B-it-abliterated.i1-IQ2_XS.gguf 3.38 GB 7c6818eb download
gemma-4-E4B-it-abliterated.i1-IQ2_XXS.gguf 3.27 GB ebc0568a download
IQ1 2 files 6.20 GB
gemma-4-E4B-it-abliterated.i1-IQ1_M.gguf 3.14 GB 6f29c9b4 download
gemma-4-E4B-it-abliterated.i1-IQ1_S.gguf 3.06 GB 8f788eab download
Auxiliary files 3 files 4.23 MB
gemma-4-E4B-it-abliterated.imatrix.gguf 4.22 MB 5afd4fac download
README.md 6.55 KB bbab3eff download
.gitattributes 3.37 KB 29819c7e download

README current version from Hugging Face


base_model: WWTCyberLab/gemma-4-E4B-it-abliterated
language:

  • en
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliteration
  • safety-research
  • alignment
  • gemma4

About

weighted/imatrix quants of https://huggingface.co/WWTCyberLab/gemma-4-E4B-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-E4B-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 3.4 for the desperate
GGUF i1-IQ1_M 3.5 mostly desperate
GGUF i1-IQ2_XXS 3.6
GGUF i1-IQ2_XS 3.7
GGUF i1-IQ2_S 3.8
GGUF i1-IQ2_M 3.9
GGUF i1-IQ3_XXS 4.1 lower quality
GGUF i1-Q2_K_S 4.4 very low quality
GGUF i1-Q2_K 4.5 IQ3_XXS probably better
GGUF i1-IQ3_XS 4.6
GGUF i1-Q3_K_S 4.8 IQ3_XS probably better
GGUF i1-IQ3_S 4.8 beats Q3_K*
GGUF i1-IQ3_M 4.8
GGUF i1-Q3_K_M 5.0 IQ3_S probably better
GGUF i1-Q3_K_L 5.1 IQ3_M probably better
GGUF i1-IQ4_XS 5.2
GGUF i1-IQ4_NL 5.3 prefer IQ4_XS
GGUF i1-Q4_0 5.3 fast, low quality
GGUF i1-Q4_K_S 5.3 optimal size/speed/quality
GGUF i1-Q4_K_M 5.4 fast, recommended
GGUF i1-Q4_1 5.5
GGUF i1-Q5_K_S 5.8
GGUF i1-Q5_K_M 5.9
GGUF i1-Q6_K 6.3 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 4 versions

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

  1. 2026-07-27auto-patch README.md8815ce06.5 KB
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  2. 2026-04-11auto-patch README.mddceb34e5.1 KB
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  3. 2026-04-10auto-patch README.mdca2889d3.1 KB
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  4. 2026-04-10uploaded from nico1f3c3781485 B
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