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

mradermacher/Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS-i1-GGUF

mradermacher Qwen 27B GGUF multimodal second-order 262K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 15,691
  • 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='KridgeDookie/Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS' (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
16K
3K last 30d - stable
Likes
5
Model age
2mo ago
created 2026-08-02
Downloads over time
Now16.6K→from9.1K↑82%
8.7K11.6K14.5K17.3K9.1K on Aug 516.6K on Oct 11AugSepOct
Aug 5 → Oct 11 · 50 snapshots · spans 67 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 · 4K downloads combined

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

Metadata

License
apache-2.0
Languages
multilingual
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf qwen qwen3.6 safetensors bfloat16 multimodal image-text-to-text text-generation abliterated uncensored refusal-reduction

Related

Total size
280 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-08-02 10:00

Files by quantization

Q6_K 1 file 20.6 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q6_K.gguf 20.6 GB df211016 download
Q5_K 2 files 35.3 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q5_K_M.gguf 17.9 GB dc10bf6d download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q5_K_S.gguf 17.4 GB f0ccb178 download
Q4 2 files 30.4 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q4_1.gguf 15.9 GB 77c115f6 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q4_0.gguf 14.5 GB 6eeb5ebc download
Q4_K 2 files 29.9 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q4_K_M.gguf 15.4 GB 01aeb389 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q4_K_S.gguf 14.5 GB 31c4b0d1 download
IQ4 1 file 14.0 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ4_XS.gguf 14.0 GB a74215cf download
Q3_K 3 files 37.0 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q3_K_L.gguf 13.4 GB 4254b587 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q3_K_M.gguf 12.4 GB d41ea9e6 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q3_K_S.gguf 11.2 GB 6c1cf19b download
IQ3 4 files 44.8 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ3_M.gguf 11.7 GB 0cf888e1 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ3_S.gguf 11.6 GB 70aa5c65 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ3_XS.gguf 11.1 GB c3093533 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ3_XXS.gguf 10.4 GB c2a1b84d download
Q2_K 2 files 19.5 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q2_K.gguf 9.98 GB ad21e1fe download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-Q2_K_S.gguf 9.54 GB 16184416 download
IQ2 4 files 34.4 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ2_M.gguf 9.32 GB 1d2113b6 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ2_S.gguf 8.72 GB 1ab3ba9e download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ2_XS.gguf 8.47 GB f3844163 download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ2_XXS.gguf 7.85 GB ad93a10d download
IQ1 2 files 13.8 GB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ1_M.gguf 7.11 GB d28b021c download
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.i1-IQ1_S.gguf 6.66 GB 220600d0 download
Auxiliary files 3 files 13.0 MB
Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS.imatrix.gguf 13.0 MB b08661ff download
README.md 7.91 KB aad56da4 download
.gitattributes 3.93 KB 9c54a703 download

README current version from Hugging Face


base_model: KridgeDookie/Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS
language:

  • multilingual
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • qwen
  • qwen3.6
  • transformers
  • safetensors
  • bfloat16
  • multimodal
  • image-text-to-text
  • text-generation
  • abliterated
  • uncensored
  • refusal-reduction

About

weighted/imatrix quants of https://huggingface.co/KridgeDookie/Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS

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

static quants are available at https://huggingface.co/mradermacher/Qwen3.6-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS-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-IQ1_S 7.2 for the desperate
GGUF i1-IQ1_M 7.7 mostly desperate
GGUF i1-IQ2_XXS 8.5
GGUF i1-IQ2_XS 9.2
GGUF i1-IQ2_S 9.5
GGUF i1-IQ2_M 10.1
GGUF i1-Q2_K_S 10.3 very low quality
GGUF i1-Q2_K 10.8 IQ3_XXS probably better
GGUF i1-IQ3_XXS 11.3 lower quality
GGUF i1-IQ3_XS 12.1
GGUF i1-Q3_K_S 12.2 IQ3_XS probably better
GGUF i1-IQ3_S 12.5 beats Q3_K*
GGUF i1-IQ3_M 12.7
GGUF i1-Q3_K_M 13.4 IQ3_S probably better
GGUF i1-Q3_K_L 14.4 IQ3_M probably better
GGUF i1-IQ4_XS 15.2
GGUF i1-Q4_0 15.6 fast, low quality
GGUF i1-Q4_K_S 15.7 optimal size/speed/quality
GGUF i1-Q4_K_M 16.6 fast, recommended
GGUF i1-Q4_1 17.2
GGUF i1-Q5_K_S 18.8
GGUF i1-Q5_K_M 19.3
GGUF i1-Q6_K 22.2 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 4 versions

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

  1. 2026-08-02auto-patch README.md37068507.9 KB
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  2. 2026-08-02auto-patch README.mdb4222326.8 KB
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  3. 2026-08-02auto-patch README.md9fbacce2.9 KB
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  4. 2026-08-02uploaded from nico170084f0512 B
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