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

mradermacher/Huihui-gemma-3n-E2B-it-abliterated-i1-GGUF

mradermacher Gemma GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 19
  • hub_downloads_all_time 8,027
  • author_summary 3327 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-3n-E2B-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
8K
1K last 30d - stable
Likes
3
Model age
12mo ago
created 2025-10-06
Downloads over time
Now8.9K→from0↑0%
03.3K6.5K9.8K0 on Jul 9, 20258.9K on Oct 12Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 9, 2025 → Oct 12 · 106 snapshots · spans 460 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 · 2K 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 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf automatic-speech-recognition automatic-speech-translation audio-text-to-text video-text-to-text abliterated uncensored en license:gemma endpoints_compatible region:us

Related

Total size
39.2 GB
Files
19
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-10-01 22:12

Files by quantization

Q6_K 1 file 3.47 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q6_K.gguf 3.47 GB 30defcf0 download
Q5_K 2 files 6.00 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q5_K_M.gguf 3.02 GB b9cfdabe download
Huihui-gemma-3n-E2B-it-abliterated.i1-Q5_K_S.gguf 2.99 GB 2dc8b976 download
Q4 2 files 5.30 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q4_1.gguf 2.76 GB 01c95398 download
Huihui-gemma-3n-E2B-it-abliterated.i1-Q4_0.gguf 2.54 GB 5978696e download
Q4_K 2 files 5.14 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q4_K_M.gguf 2.60 GB 79969c7c download
Huihui-gemma-3n-E2B-it-abliterated.i1-Q4_K_S.gguf 2.54 GB 34466601 download
IQ4 2 files 4.97 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-IQ4_NL.gguf 2.54 GB 017a1253 download
Huihui-gemma-3n-E2B-it-abliterated.i1-IQ4_XS.gguf 2.43 GB d0867636 download
Q3_K 3 files 6.42 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q3_K_L.gguf 2.22 GB 1b4629f8 download
Huihui-gemma-3n-E2B-it-abliterated.i1-Q3_K_M.gguf 2.14 GB 4b889300 download
Huihui-gemma-3n-E2B-it-abliterated.i1-Q3_K_S.gguf 2.06 GB 62c01133 download
IQ3 3 files 6.17 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-IQ3_M.gguf 2.08 GB c8f8b98c download
Huihui-gemma-3n-E2B-it-abliterated.i1-IQ3_S.gguf 2.06 GB 994ab2f4 download
Huihui-gemma-3n-E2B-it-abliterated.i1-IQ3_XS.gguf 2.02 GB 0ec77a40 download
Q2_K 1 file 1.76 GB
Huihui-gemma-3n-E2B-it-abliterated.i1-Q2_K.gguf 1.76 GB f029fc9c download
Auxiliary files 3 files 3.00 MB
Huihui-gemma-3n-E2B-it-abliterated.imatrix.gguf 2.99 MB 19814018 download
README.md 5.95 KB e792a470 download
.gitattributes 2.90 KB 700d8149 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-gemma-3n-E2B-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-E2B-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-E2B-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 imatrix 0.1 imatrix file (for creating your own quants)
GGUF i1-Q2_K 2.0 IQ3_XXS probably better
GGUF i1-IQ3_XS 2.3
GGUF i1-Q3_K_S 2.3 IQ3_XS probably better
GGUF i1-IQ3_S 2.3 beats Q3_K*
GGUF i1-IQ3_M 2.3
GGUF i1-Q3_K_M 2.4 IQ3_S probably better
GGUF i1-Q3_K_L 2.5 IQ3_M probably better
GGUF i1-IQ4_XS 2.7
GGUF i1-Q4_0 2.8 fast, low quality
GGUF i1-IQ4_NL 2.8 prefer IQ4_XS
GGUF i1-Q4_K_S 2.8 optimal size/speed/quality
GGUF i1-Q4_K_M 2.9 fast, recommended
GGUF i1-Q4_1 3.1
GGUF i1-Q5_K_S 3.3
GGUF i1-Q5_K_M 3.3
GGUF i1-Q6_K 3.8 practically like static Q6_K

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.

README history 6 versions

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

  1. 2026-10-01auto-patch README.md3e508205.8 KB
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  2. 2026-02-03auto-patch README.md3a567226 KB
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  3. 2025-12-05auto-patch README.md72cbf4e5.8 KB
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  4. 2025-10-06auto-patch README.md30ad8135.8 KB
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  5. 2025-10-06auto-patch README.mdc1559042.9 KB
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  6. 2025-10-06uploaded from rich1a2f023c490 B
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