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mradermacher/Gemma-3-Prompt-Coder-270m-it-Uncensored-GGUF

mradermacher Gemma GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FGemma-3-Prompt-Coder-270m-it-Uncensored-GGUF"
Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 5,923
  • 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='WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m' (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.

What is a refusal direction? →
Downloads · lifetime
6K
702 last 30d - stable
Likes
4
Model age
8mo ago
created 2026-02-07

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now6.2K→from1.2K↑434%
9152.9K4.8K6.8K1.2K on Feb 116.2K on Oct 11FebAprJunAugOct
Feb 11 → Oct 11 · 74 snapshots · spans 242 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.

Metadata

Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf mergekit merge en dataset:microsoft/rStar-Coder dataset:gokaygokay/prompt-enhancement-75k dataset:gokaygokay/prompt-enhancer-dataset base_model:WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m base_model:quantized:WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m endpoints_compatible region:us

Related

Total size
3.11 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-04-25 02:52

Files by quantization

F16 1 file 518 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.f16.gguf 518 MB 8ec119da download
Q8_0 1 file 278 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q8_0.gguf 278 MB 6fa81b70 download
Q6_K 1 file 270 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q6_K.gguf 270 MB 01fa57d1 download
Q5_K 2 files 494 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q5_K_M.gguf 248 MB 08001707 download
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q5_K_S.gguf 246 MB 9c8026b0 download
Q4_K 2 files 480 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q4_K_M.gguf 241 MB 05c1e58b download
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q4_K_S.gguf 238 MB 77c64f98 download
Q3_K 3 files 691 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q3_K_L.gguf 235 MB b78b2fbb download
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q3_K_M.gguf 231 MB 52b75ac3 download
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q3_K_S.gguf 226 MB cbdd7145 download
IQ4 1 file 230 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.IQ4_XS.gguf 230 MB 88164335 download
Q2_K 1 file 226 MB
Gemma-3-Prompt-Coder-270m-it-Uncensored.Q2_K.gguf 226 MB 8ad09c44 download
Auxiliary files 2 files 6.78 KB
README.md 4.28 KB 1445da32 download
.gitattributes 2.51 KB 6f69c61f download

README current version from Hugging Face


base_model: WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m
datasets:

  • microsoft/rStar-Coder
  • gokaygokay/prompt-enhancement-75k
  • gokaygokay/prompt-enhancer-dataset
    language:
  • en
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • mergekit
  • merge

About

static quants of https://huggingface.co/WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 Q3_K_S 0.3
GGUF Q2_K 0.3
GGUF IQ4_XS 0.3
GGUF Q3_K_M 0.3 lower quality
GGUF Q3_K_L 0.3
GGUF Q4_K_S 0.3 fast, recommended
GGUF Q4_K_M 0.4 fast, recommended
GGUF Q5_K_S 0.4
GGUF Q5_K_M 0.4
GGUF Q6_K 0.4 very good quality
GGUF Q8_0 0.4 fast, best quality
GGUF f16 0.6 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. 2026-04-25auto-patch README.md962509d4.3 KB
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  2. 2026-03-03auto-patch README.md2788cfa4.3 KB
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  3. 2026-02-07auto-patch README.md16357ba4.3 KB
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  4. 2026-02-07uploaded from leia89ce1b7390 B
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