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mradermacher/gemma-4-E4B-it-ultra-uncensored-heretic-GGUF

mradermacher Gemma GGUF second-order 131K ctx
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Response includes
  • classification m3
  • files 16
  • benchmarks 11 entries
  • hub_downloads_all_time 23,238
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
23K
3K last 30d - stable
Likes
8
Model age
6mo ago
created 2026-04-07
Downloads over time
Now24.4K→from0↑0%
08.9K17.9K26.8K0 on Apr 824.4K on Oct 11AprMayJunJulAugSepOct
Apr 8 → Oct 11 · 67 snapshots · spans 186 days

Benchmarks

Benchmark Score Source
Entertainment 0.9 UGI
Hazardous 1.2 UGI
Natural Intelligence 16.7 UGI
Political lean -13.3% UGI
Sensitive-Info 10.94 UGI
SocPol 1.3 UGI
UGI 38.12 UGI
Willingness (10) 9.2 UGI
W10-Adherence 8.5 UGI
W10-Direct 10 UGI
Writing 19.06 UGI

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 · 8K 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 heretic uncensored decensored abliterated ara en base_model:llmfan46/gemma-4-E4B-it-ultra-uncensored-heretic base_model:quantized:llmfan46/gemma-4-E4B-it-ultra-uncensored-heretic license:apache-2.0 endpoints_compatible

Related

Total size
70.1 GB
Files
16
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-04-07 07:46

Files by quantization

F16 2 files 14.9 GB
gemma-4-E4B-it-ultra-uncensored-heretic.f16.gguf 14.0 GB 705d47ec download
gemma-4-E4B-it-ultra-uncensored-heretic.mmproj-f16.gguf 944 MB 065e6cf0 download
Q8_0 2 files 8.00 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q8_0.gguf 7.48 GB 9901800b download
gemma-4-E4B-it-ultra-uncensored-heretic.mmproj-Q8_0.gguf 534 MB fe552c27 download
Q6_K 1 file 5.79 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q6_K.gguf 5.79 GB b582b587 download
Q5_K 2 files 10.7 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q5_K_M.gguf 5.37 GB 8caf51d6 download
gemma-4-E4B-it-ultra-uncensored-heretic.Q5_K_S.gguf 5.30 GB f3a9fe05 download
Q4_K 2 files 9.81 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q4_K_M.gguf 4.97 GB f18b5f11 download
gemma-4-E4B-it-ultra-uncensored-heretic.Q4_K_S.gguf 4.85 GB 611f7551 download
IQ4 1 file 4.74 GB
gemma-4-E4B-it-ultra-uncensored-heretic.IQ4_XS.gguf 4.74 GB 8c4386f1 download
Q3_K 3 files 13.5 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q3_K_L.gguf 4.68 GB 324b27b3 download
gemma-4-E4B-it-ultra-uncensored-heretic.Q3_K_M.gguf 4.52 GB 6786c86f download
gemma-4-E4B-it-ultra-uncensored-heretic.Q3_K_S.gguf 4.33 GB f24c40b4 download
Q2_K 1 file 4.10 GB
gemma-4-E4B-it-ultra-uncensored-heretic.Q2_K.gguf 4.10 GB a6e3355f download
Auxiliary files 2 files 7.28 KB
README.md 4.59 KB 8d33d5d7 download
.gitattributes 2.69 KB 79f59ce0 download

README current version from Hugging Face


base_model: llmfan46/gemma-4-E4B-it-ultra-uncensored-heretic
language:


About

static quants of https://huggingface.co/llmfan46/gemma-4-E4B-it-ultra-uncensored-heretic

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-E4B-it-ultra-uncensored-heretic-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 4.5
GGUF Q3_K_S 4.8
GGUF Q3_K_M 5.0 lower quality
GGUF Q3_K_L 5.1
GGUF IQ4_XS 5.2
GGUF Q4_K_S 5.3 fast, recommended
GGUF Q4_K_M 5.4 fast, recommended
GGUF Q5_K_S 5.8
GGUF Q5_K_M 5.9
GGUF Q6_K 6.3 very good quality
GGUF Q8_0 8.1 fast, best quality
GGUF f16 15.2 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. 2026-04-07auto-patch README.md938c9ab4.6 KB
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  2. 2026-04-07auto-patch README.mdcd75d164.7 KB
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  3. 2026-04-07auto-patch README.md0f82c824.5 KB
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  4. 2026-04-07uploaded from nico1d109fd8391 B
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