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mradermacher/gemma4-alpaca-uncensored-GGUF

mradermacher Gemma GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 16
  • hub_downloads_all_time 1,467
  • 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='renierd6/gemma4-alpaca-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
1K
258 last 30d - stable
Likes
1
Model age
6mo ago
created 2026-04-13
Downloads over time
Now1.5K→from915↑65%
8851.1K1.3K1.6K915 on Apr 151.5K on Oct 111.5K on Oct 10AprMayJunJulAugSepOct
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 · 632 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
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf text-generation-inference unsloth gemma4 en license:apache-2.0 endpoints_compatible region:us conversational

Related

Total size
44.7 GB
Files
16
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-04-14 14:21

Files by quantization

F16 2 files 9.59 GB
gemma4-alpaca-uncensored.f16.gguf 8.67 GB e2bd86e7 download
gemma4-alpaca-uncensored.mmproj-f16.gguf 940 MB 75742d22 download
Q8_0 2 files 5.15 GB
gemma4-alpaca-uncensored.Q8_0.gguf 4.63 GB e3f94930 download
gemma4-alpaca-uncensored.mmproj-Q8_0.gguf 532 MB 94e08f7b download
Q6_K 1 file 3.58 GB
gemma4-alpaca-uncensored.Q6_K.gguf 3.58 GB 29dfecb5 download
Q5_K 2 files 6.73 GB
gemma4-alpaca-uncensored.Q5_K_M.gguf 3.38 GB fbccce84 download
gemma4-alpaca-uncensored.Q5_K_S.gguf 3.35 GB e41643e6 download
Q4_K 2 files 6.33 GB
gemma4-alpaca-uncensored.Q4_K_M.gguf 3.19 GB a5a71dd1 download
gemma4-alpaca-uncensored.Q4_K_S.gguf 3.13 GB 0211c1b4 download
IQ4 1 file 3.08 GB
gemma4-alpaca-uncensored.IQ4_XS.gguf 3.08 GB 54fa1b30 download
Q3_K 3 files 8.94 GB
gemma4-alpaca-uncensored.Q3_K_L.gguf 3.06 GB 034953fc download
gemma4-alpaca-uncensored.Q3_K_M.gguf 2.98 GB e285ec83 download
gemma4-alpaca-uncensored.Q3_K_S.gguf 2.90 GB bcdee880 download
Q2_K 1 file 2.78 GB
gemma4-alpaca-uncensored.Q2_K.gguf 2.78 GB 24a81efa download
Auxiliary files 2 files 6.55 KB
README.md 4.07 KB f2d2e39f download
.gitattributes 2.48 KB c35e8367 download

README current version from Hugging Face


base_model: renierd6/gemma4-alpaca-uncensored
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • text-generation-inference
  • transformers
  • unsloth
  • gemma4

About

static quants of https://huggingface.co/renierd6/gemma4-alpaca-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/gemma4-alpaca-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 mmproj-Q8_0 0.7 multi-modal supplement
GGUF mmproj-f16 1.1 multi-modal supplement
GGUF Q2_K 3.1
GGUF Q3_K_S 3.2
GGUF Q3_K_M 3.3 lower quality
GGUF Q3_K_L 3.4
GGUF IQ4_XS 3.4
GGUF Q4_K_S 3.5 fast, recommended
GGUF Q4_K_M 3.5 fast, recommended
GGUF Q5_K_S 3.7
GGUF Q5_K_M 3.7
GGUF Q6_K 3.9 very good quality
GGUF Q8_0 5.1 fast, best quality
GGUF f16 9.4 16 bpw, overkill

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. 2026-04-14auto-patch README.mdd7ea6bf4.1 KB
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  2. 2026-04-13auto-patch README.mdd5b4ffc4.2 KB
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  3. 2026-04-13auto-patch README.mda43e5f82.4 KB
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  4. 2026-04-13uploaded from nico15465f3d376 B
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