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mradermacher/Huihui-gemma-3n-E4B-it-abliterated-i1-GGUF

mradermacher Gemma GGUF second-order
curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FHuihui-gemma-3n-E4B-it-abliterated-i1-GGUF"
Response includes
  • classification m8
  • files 6
  • author_summary 3243 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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-3n-E4B-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.

What is a refusal direction? →
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Model age
today
created 2026-09-20

Genealogy 0 direct forks

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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
Quantizations
IQ3 Q2_K Q4_K
Tags
transformers gguf automatic-speech-recognition automatic-speech-translation audio-text-to-text video-text-to-text abliterated uncensored en base_model:huihui-ai/Huihui-gemma-3n-E4B-it-abliterated base_model:quantized:huihui-ai/Huihui-gemma-3n-E4B-it-abliterated license:gemma

Related

Total size
12.0 GB
Files
6
Quantizations
4
Registered
2026-09-20 00:56
Last updated on HF
2026-09-20 00:56

Files by quantization

Q4_K 1 file 4.39 GB
Huihui-gemma-3n-E4B-it-abliterated.i1-Q4_K_S.gguf 4.39 GB a4e45cf1 download
IQ3 1 file 3.92 GB
Huihui-gemma-3n-E4B-it-abliterated.i1-IQ3_M.gguf 3.92 GB ae281b87 download
Q2_K 1 file 3.65 GB
Huihui-gemma-3n-E4B-it-abliterated.i1-Q2_K.gguf 3.65 GB e2c8b393 download
Auxiliary files 3 files 4.48 MB
imatrix.dat 4.47 MB 97e948f2 download
README.md 3.39 KB a448c13f download
.gitattributes 1.78 KB f6ffe6aa download

README current version from Hugging Face


base_model: huihui-ai/Huihui-gemma-3n-E4B-it-abliterated
extra_gated_button_content: Acknowledge license
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
Face and click below. Requests are processed immediately.
language:

  • en
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • automatic-speech-recognition
  • automatic-speech-translation
  • audio-text-to-text
  • video-text-to-text
  • abliterated
  • uncensored

About

weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-gemma-3n-E4B-it-abliterated

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

static quants are available at https://huggingface.co/mradermacher/Huihui-gemma-3n-E4B-it-abliterated-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 i1-Q2_K 4.0 IQ3_XXS probably better
GGUF i1-IQ3_M 4.3
GGUF i1-Q4_K_S 4.8 optimal size/speed/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. 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.

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