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mradermacher/Qwopus3.5-27B-v3-Abliterated-i1-GGUF

mradermacher 27B GGUF second-order
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curl -H "Authorization: Bearer $ABL_KEY" \
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Response includes
  • classification m8
  • files 15
  • author_summary 3376 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='croll83/Qwopus3.5-27B-v3-Abliterated' (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.

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Downloads · 30-day
0
Likes
1
Model age
today
created 2026-10-21

Genealogy 0 direct forks

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Variants by this author 2 formats · 3 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 it zh
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4_K Q6_K
Tags
transformers gguf qwen3_5 qwopus abliterated uncensored Claude reasoning chain-of-thought conversational en it

Related

Total size
146 GB
Files
15
Quantizations
9
Registered
2026-10-21 10:00
Last updated on HF
2026-10-21 11:17

Files by quantization

Q6_K 1 file 20.6 GB
Qwopus3.5-27B-v3-Abliterated.i1-Q6_K.gguf 20.6 GB df0dfa93 download
Q4_K 2 files 29.9 GB
Qwopus3.5-27B-v3-Abliterated.i1-Q4_K_M.gguf 15.4 GB dfea4f01 download
Qwopus3.5-27B-v3-Abliterated.i1-Q4_K_S.gguf 14.5 GB 6706880b download
IQ4 1 file 14.0 GB
Qwopus3.5-27B-v3-Abliterated.i1-IQ4_XS.gguf 14.0 GB 80d1381c download
Q3_K 2 files 23.6 GB
Qwopus3.5-27B-v3-Abliterated.i1-Q3_K_M.gguf 12.4 GB a67ad75b download
Qwopus3.5-27B-v3-Abliterated.i1-Q3_K_S.gguf 11.2 GB 5df4a5ca download
IQ3 2 files 22.1 GB
Qwopus3.5-27B-v3-Abliterated.i1-IQ3_M.gguf 11.7 GB 19495c4e download
Qwopus3.5-27B-v3-Abliterated.i1-IQ3_XXS.gguf 10.4 GB 335a461b download
Q2_K 2 files 19.5 GB
Qwopus3.5-27B-v3-Abliterated.i1-Q2_K.gguf 9.98 GB a31c3c8b download
Qwopus3.5-27B-v3-Abliterated.i1-Q2_K_S.gguf 9.54 GB 3de8fcfa download
IQ2 1 file 9.32 GB
Qwopus3.5-27B-v3-Abliterated.i1-IQ2_M.gguf 9.32 GB 887e016d download
IQ1 1 file 7.11 GB
Qwopus3.5-27B-v3-Abliterated.i1-IQ1_M.gguf 7.11 GB f0ce15e4 download
Auxiliary files 3 files 26.0 MB
Qwopus3.5-27B-v3-Abliterated.imatrix.gguf 26.0 MB 1ed4cc36 download
README.md 2.85 KB 919eb636 download
.gitattributes 2.49 KB 5d29fba8 download

README current version from Hugging Face


base_model: croll83/Qwopus3.5-27B-v3-Abliterated
language:

  • en
  • it
  • zh
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • qwen3_5
  • qwopus
  • abliterated
  • uncensored
  • Claude
  • reasoning
  • chain-of-thought
  • conversational
  • gguf

About

weighted/imatrix quants of https://huggingface.co/croll83/Qwopus3.5-27B-v3-Abliterated

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

static quants are available at https://huggingface.co/mradermacher/Qwopus3.5-27B-v3-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 10.8 IQ3_XXS probably better

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.

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