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mradermacher/survival-uncensored-gemma-270m-v2-GGUF

mradermacher Gemma GGUF second-order 33K ctx
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Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 4,516
  • 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='pixasocial/survival-uncensored-gemma-270m-v2' (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
5K
436 last 30d - cooling
Likes
2
Model age
13mo ago
created 2025-09-09
Downloads over time
Now4.6K→from1.3K↑247%
1.2K2.4K3.7K4.9K1.3K on Sep 10, 20254.6K on Oct 11Sep '25Nov '25JanMarMayJulSep
Sep 10, 2025 → Oct 11 · 96 snapshots · spans 396 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 · 1K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
mit
Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf base_model:adapter:google/gemma-3-270m-it lora survival marketing psychology warfare stoicism history roleplay personas

Related

Total size
3.11 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-09-09 04:24

Files by quantization

F16 1 file 518 MB
survival-uncensored-gemma-270m-v2.f16.gguf 518 MB dfd3411e download
Q8_0 1 file 278 MB
survival-uncensored-gemma-270m-v2.Q8_0.gguf 278 MB b88fa38e download
Q6_K 1 file 270 MB
survival-uncensored-gemma-270m-v2.Q6_K.gguf 270 MB 8aa09e08 download
Q5_K 2 files 494 MB
survival-uncensored-gemma-270m-v2.Q5_K_M.gguf 248 MB b1873a2f download
survival-uncensored-gemma-270m-v2.Q5_K_S.gguf 246 MB 11c9ac4c download
Q4_K 2 files 480 MB
survival-uncensored-gemma-270m-v2.Q4_K_M.gguf 241 MB 8c57ae38 download
survival-uncensored-gemma-270m-v2.Q4_K_S.gguf 238 MB 641493bf download
Q3_K 3 files 691 MB
survival-uncensored-gemma-270m-v2.Q3_K_L.gguf 235 MB 12f3f4ed download
survival-uncensored-gemma-270m-v2.Q3_K_M.gguf 231 MB b1707517 download
survival-uncensored-gemma-270m-v2.Q3_K_S.gguf 226 MB 459ab55f download
IQ4 1 file 230 MB
survival-uncensored-gemma-270m-v2.IQ4_XS.gguf 230 MB af7ab6c3 download
Q2_K 1 file 226 MB
survival-uncensored-gemma-270m-v2.Q2_K.gguf 226 MB abb83095 download
Auxiliary files 2 files 6.52 KB
README.md 4.08 KB 9d6bef2e download
.gitattributes 2.44 KB e3bec644 download

README current version from Hugging Face


base_model: pixasocial/survival-uncensored-gemma-270m-v2
language:

  • en
    library_name: transformers
    license: mit
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • base_model:adapter:google/gemma-3-270m-it
  • lora
  • transformers
  • survival
  • marketing
  • psychology
  • warfare
  • stoicism
  • history
  • roleplay
  • personas
  • conversation
  • micromodels

About

static quants of https://huggingface.co/pixasocial/survival-uncensored-gemma-270m-v2

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/survival-uncensored-gemma-270m-v2-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 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 2 versions

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

  1. 2025-09-09auto-patch README.mdb40bf9d4.1 KB
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  2. 2025-09-09uploaded from rich1522459f386 B
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