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mradermacher/Ada-Gemma-4-26B-A4B-it-abliterated-GGUF

mradermacher Gemma 26B GGUF MoE second-order 262K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 1,836
  • 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='SevenOfNine/Gemma-4-26B-A4B-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.

What is a refusal direction? →
Downloads · lifetime
2K
404 last 30d - stable
Likes
2
Model age
4mo ago
created 2026-06-11
Downloads over time
Now1.9K→from531↑259%
4629901.5K2K531 on Jun 101.9K on Oct 11JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 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 · 1K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
gemma
Languages
en fr
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored heretic gemma4 moe en fr base_model:SevenOfNine/Gemma-4-26B-A4B-It-Abliterated base_model:quantized:SevenOfNine/Gemma-4-26B-A4B-It-Abliterated license:gemma

Related

Total size
170 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2026-06-11 06:48

Files by quantization

Q8_0 1 file 25.0 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q8_0.gguf 25.0 GB 6b0463e2 download
Q6_K 1 file 21.1 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q6_K.gguf 21.1 GB 00946632 download
Q5_K 2 files 34.6 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q5_K_M.gguf 17.8 GB e9270429 download
Ada-Gemma-4-26B-A4B-it-abliterated.Q5_K_S.gguf 16.8 GB 268c4227 download
Q4_K 2 files 30.0 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q4_K_M.gguf 15.6 GB 03f8be0a download
Ada-Gemma-4-26B-A4B-it-abliterated.Q4_K_S.gguf 14.4 GB c0bd77e8 download
IQ4 1 file 13.1 GB
Ada-Gemma-4-26B-A4B-it-abliterated.IQ4_XS.gguf 13.1 GB 7ec8aed8 download
Q3_K 3 files 36.6 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q3_K_L.gguf 12.9 GB d1834323 download
Ada-Gemma-4-26B-A4B-it-abliterated.Q3_K_M.gguf 12.4 GB a60b1284 download
Ada-Gemma-4-26B-A4B-it-abliterated.Q3_K_S.gguf 11.4 GB 758011f0 download
Q2_K 1 file 9.86 GB
Ada-Gemma-4-26B-A4B-it-abliterated.Q2_K.gguf 9.86 GB 80932dcc download
Auxiliary files 2 files 6.19 KB
README.md 3.82 KB 40f0fb90 download
.gitattributes 2.37 KB 09b0a785 download

README current version from Hugging Face


base_model: SevenOfNine/Gemma-4-26B-A4B-It-Abliterated
language:

  • en
  • fr
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • heretic
  • gemma4
  • moe

About

static quants of https://huggingface.co/SevenOfNine/Gemma-4-26B-A4B-It-Abliterated

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Ada-Gemma-4-26B-A4B-it-abliterated-i1-GGUF

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 Q2_K 10.7
GGUF Q3_K_S 12.3
GGUF Q3_K_M 13.4 lower quality
GGUF Q3_K_L 13.9
GGUF IQ4_XS 14.2
GGUF Q4_K_S 15.6 fast, recommended
GGUF Q4_K_M 16.9 fast, recommended
GGUF Q5_K_S 18.1
GGUF Q5_K_M 19.2
GGUF Q6_K 22.7 very good quality
GGUF Q8_0 27.0 fast, best quality

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.

README history 4 versions

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

  1. 2026-06-11auto-patch README.md308ba673.8 KB
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  2. 2026-06-11auto-patch README.mdc47b27e3.9 KB
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  3. 2026-06-11auto-patch README.mdbee4f2a3.8 KB
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  4. 2026-06-11uploaded from nico1ca1545a390 B
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