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mradermacher/gemma-4-E2B-it-uncensored-i1-GGUF

mradermacher Gemma GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 18
  • hub_downloads_all_time 7,987
  • 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='TrevorJS/gemma-4-E2B-it-uncensored' (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
8K
826 last 30d - stable
Likes
1
Model age
6mo ago
created 2026-04-10
Downloads over time
Now8.2K→from4.9K↑69%
4.7K6K7.3K8.6K4.9K on Apr 158.2K on Oct 11AprMayJunJulAugSepOct
Apr 15 → Oct 11 · 65 snapshots · spans 179 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
apache-2.0
Languages
en
Quantizations
IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf abliteration uncensored gemma-4 en base_model:TrevorJS/gemma-4-E2B-it-uncensored base_model:quantized:TrevorJS/gemma-4-E2B-it-uncensored license:apache-2.0 endpoints_compatible region:us imatrix

Related

Total size
46.8 GB
Files
18
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-04-11 07:27

Files by quantization

Q6_K 1 file 3.58 GB
gemma-4-E2B-it-uncensored.i1-Q6_K.gguf 3.58 GB 81e8656f download
Q5_K 2 files 6.73 GB
gemma-4-E2B-it-uncensored.i1-Q5_K_M.gguf 3.38 GB 26dac557 download
gemma-4-E2B-it-uncensored.i1-Q5_K_S.gguf 3.35 GB b27575fe download
Q4 2 files 6.37 GB
gemma-4-E2B-it-uncensored.i1-Q4_1.gguf 3.24 GB 616e0d18 download
gemma-4-E2B-it-uncensored.i1-Q4_0.gguf 3.13 GB d2caadf7 download
Q4_K 2 files 6.33 GB
gemma-4-E2B-it-uncensored.i1-Q4_K_M.gguf 3.19 GB 94c21f53 download
gemma-4-E2B-it-uncensored.i1-Q4_K_S.gguf 3.13 GB e64085ec download
IQ4 2 files 6.21 GB
gemma-4-E2B-it-uncensored.i1-IQ4_NL.gguf 3.13 GB e56e7866 download
gemma-4-E2B-it-uncensored.i1-IQ4_XS.gguf 3.08 GB 349dfb44 download
Q3_K 3 files 8.94 GB
gemma-4-E2B-it-uncensored.i1-Q3_K_L.gguf 3.06 GB b78d2dd2 download
gemma-4-E2B-it-uncensored.i1-Q3_K_M.gguf 2.98 GB 100be7d1 download
gemma-4-E2B-it-uncensored.i1-Q3_K_S.gguf 2.90 GB 3a53ec07 download
IQ3 2 files 5.82 GB
gemma-4-E2B-it-uncensored.i1-IQ3_M.gguf 2.92 GB 881bdf59 download
gemma-4-E2B-it-uncensored.i1-IQ3_S.gguf 2.90 GB 1cc3ad5d download
Q2_K 1 file 2.78 GB
gemma-4-E2B-it-uncensored.i1-Q2_K.gguf 2.78 GB 425fb253 download
Auxiliary files 3 files 2.70 MB
gemma-4-E2B-it-uncensored.imatrix.gguf 2.69 MB efa37cc5 download
README.md 5.04 KB 1d72a78e download
.gitattributes 2.67 KB f8f26684 download

README current version from Hugging Face


base_model: TrevorJS/gemma-4-E2B-it-uncensored
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliteration
  • uncensored
  • gemma-4

About

weighted/imatrix quants of https://huggingface.co/TrevorJS/gemma-4-E2B-it-uncensored

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-E2B-it-uncensored-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-Q2_K 3.1 IQ3_XXS probably better
GGUF i1-Q3_K_S 3.2 IQ3_XS probably better
GGUF i1-IQ3_S 3.2 beats Q3_K*
GGUF i1-IQ3_M 3.2
GGUF i1-Q3_K_M 3.3 IQ3_S probably better
GGUF i1-Q3_K_L 3.4 IQ3_M probably better
GGUF i1-IQ4_XS 3.4
GGUF i1-IQ4_NL 3.5 prefer IQ4_XS
GGUF i1-Q4_0 3.5 fast, low quality
GGUF i1-Q4_K_S 3.5 optimal size/speed/quality
GGUF i1-Q4_K_M 3.5 fast, recommended
GGUF i1-Q4_1 3.6
GGUF i1-Q5_K_S 3.7
GGUF i1-Q5_K_M 3.7
GGUF i1-Q6_K 3.9 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. 2026-04-11auto-patch README.md34851ef5 KB
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  2. 2026-04-10auto-patch README.md2fa42b22.6 KB
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  3. 2026-04-10uploaded from nico1b333f49481 B
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