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

mradermacher/Huihui-gemma-4-31B-it-abliterated-GGUF

mradermacher Gemma 31B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 9,512
  • 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 layer-wise ablation 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='huihui-ai/Huihui-gemma-4-31B-it-abliterated' (base is huihui-ai model (M3))
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
10K
2K last 30d - stable
Likes
1
Model age
5mo ago
created 2026-04-17
Downloads over time
Now10.5K→from833↑1,159%
3504.1K7.8K11.5K833 on Apr 1510.5K 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 · 4K 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
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored en base_model:huihui-ai/Huihui-gemma-4-31B-it-abliterated base_model:quantized:huihui-ai/Huihui-gemma-4-31B-it-abliterated license:apache-2.0 endpoints_compatible region:us conversational

Related

Total size
197 GB
Files
15
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-10-07 16:12

Files by quantization

Q8_0 2 files 31.1 GB
Huihui-gemma-4-31B-it-abliterated.Q8_0.gguf 30.4 GB 3c9c0953 download
Huihui-gemma-4-31B-it-abliterated.mmproj-Q8_0.gguf 772 MB 2f2acbb1 download
Q6_K 1 file 23.5 GB
Huihui-gemma-4-31B-it-abliterated.Q6_K.gguf 23.5 GB 689e928a download
Q5_K 2 files 40.2 GB
Huihui-gemma-4-31B-it-abliterated.Q5_K_M.gguf 20.3 GB 702c81e6 download
Huihui-gemma-4-31B-it-abliterated.Q5_K_S.gguf 19.8 GB 3f1b4d4f download
Q4_K 2 files 33.9 GB
Huihui-gemma-4-31B-it-abliterated.Q4_K_M.gguf 17.4 GB 1d11fb88 download
Huihui-gemma-4-31B-it-abliterated.Q4_K_S.gguf 16.5 GB 64a3eca9 download
IQ4 1 file 15.7 GB
Huihui-gemma-4-31B-it-abliterated.IQ4_XS.gguf 15.7 GB 8a5fa2cf download
Q3_K 3 files 42.5 GB
Huihui-gemma-4-31B-it-abliterated.Q3_K_L.gguf 15.5 GB d7b0fdf7 download
Huihui-gemma-4-31B-it-abliterated.Q3_K_M.gguf 14.2 GB 287542ac download
Huihui-gemma-4-31B-it-abliterated.Q3_K_S.gguf 12.8 GB 30bd1864 download
Q2_K 1 file 11.1 GB
Huihui-gemma-4-31B-it-abliterated.Q2_K.gguf 11.1 GB e6fb062e download
F16 1 file 1.12 GB
Huihui-gemma-4-31B-it-abliterated.mmproj-f16.gguf 1.12 GB e22d6c09 download
Auxiliary files 2 files 6.75 KB
README.md 4.22 KB 9161ee38 download
.gitattributes 2.53 KB e4254420 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-gemma-4-31B-it-abliterated
language:


About

static quants of https://huggingface.co/huihui-ai/Huihui-gemma-4-31B-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/Huihui-gemma-4-31B-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 mmproj-Q8_0 0.9 multi-modal supplement
GGUF mmproj-f16 1.3 multi-modal supplement
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. 2026-10-07auto-patch README.md0ba2fa84.4 KB
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  2. 2026-04-18auto-patch README.md8cb0c5e4.2 KB
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  3. 2026-04-17auto-patch README.mda3f1d794.3 KB
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  4. 2026-04-17auto-patch README.md873ea094.2 KB
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  5. 2026-04-17uploaded from nico18912f28386 B
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