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mradermacher/Gemma-4-31B-Abliterated-Uncensored-GGUF

mradermacher Gemma 31B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 5,061
  • author_summary 3379 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='Madras1/Gemma-4-31B-Abliterated-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
5K
2K last 30d - stable
Likes
2
Model age
6w ago
created 2026-09-06
Downloads over time
Now6.6K→from0↑0%
02.4K4.9K7.3K0 on Sep 66.6K on Oct 21SepOct
Sep 6 → Oct 21 · 46 snapshots · spans 45 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 · 6K downloads combined

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

Metadata

License
apache-2.0
Languages
pt en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored representation-engineering gemma-4 google-deepmind creative-writing roleplay text-generation pt en

Related

Total size
197 GB
Files
13
Quantizations
8
Registered
2026-09-06 13:55
Last updated on HF
2026-10-10 17:16

Files by quantization

Q8_0 1 file 30.4 GB
Gemma-4-31B-Abliterated-Uncensored.Q8_0.gguf 30.4 GB 255032a1 download
Q6_K 1 file 23.5 GB
Gemma-4-31B-Abliterated-Uncensored.Q6_K.gguf 23.5 GB e05c9eb0 download
Q5_K 2 files 40.2 GB
Gemma-4-31B-Abliterated-Uncensored.Q5_K_M.gguf 20.3 GB c097fac0 download
Gemma-4-31B-Abliterated-Uncensored.Q5_K_S.gguf 19.8 GB 5415c8e9 download
Q4_K 2 files 33.9 GB
Gemma-4-31B-Abliterated-Uncensored.Q4_K_M.gguf 17.4 GB 374d9021 download
Gemma-4-31B-Abliterated-Uncensored.Q4_K_S.gguf 16.5 GB 9df865fd download
IQ4 1 file 15.7 GB
Gemma-4-31B-Abliterated-Uncensored.IQ4_XS.gguf 15.7 GB bd3a708f download
Q3_K 3 files 42.5 GB
Gemma-4-31B-Abliterated-Uncensored.Q3_K_L.gguf 15.5 GB 3cdfdfe1 download
Gemma-4-31B-Abliterated-Uncensored.Q3_K_M.gguf 14.2 GB 6520068d download
Gemma-4-31B-Abliterated-Uncensored.Q3_K_S.gguf 12.8 GB 6a4ce72c download
Q2_K 1 file 11.1 GB
Gemma-4-31B-Abliterated-Uncensored.Q2_K.gguf 11.1 GB 0ff39166 download
Auxiliary files 2 files 6.28 KB
README.md 3.91 KB 321ebdd1 download
.gitattributes 2.37 KB 71175ac5 download

README current version from Hugging Face


base_model: Madras1/Gemma-4-31B-Abliterated-Uncensored
language:

  • pt
  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • representation-engineering
  • gemma-4
  • google-deepmind
  • creative-writing
  • roleplay
  • text-generation

About

static quants of https://huggingface.co/Madras1/Gemma-4-31B-Abliterated-Uncensored

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma-4-31B-Abliterated-Uncensored-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 12.0
GGUF Q3_K_S 13.9
GGUF Q3_K_M 15.4 lower quality
GGUF Q3_K_L 16.7
GGUF IQ4_XS 17.0
GGUF Q4_K_S 17.9 fast, recommended
GGUF Q4_K_M 18.8 fast, recommended
GGUF Q5_K_S 21.4
GGUF Q5_K_M 21.9
GGUF Q6_K 25.3 very good quality
GGUF Q8_0 32.7 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 5 versions

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

  1. 2026-10-10auto-patch README.md3288ba44.1 KB
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  2. 2026-09-06auto-patch README.md999ee023.9 KB
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  3. 2026-09-06auto-patch README.mdd7ed77c3.7 KB
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  4. 2026-09-06auto-patch README.md1283ff43.2 KB
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  5. 2026-09-06uploaded from nico1f175ae8386 B
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