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

mradermacher 27B GGUF second-order
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FQwopus3.5-27B-v3-Abliterated-GGUF"
Response includes
  • classification m8
  • files 13
  • author_summary 3371 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.

What is a refusal direction? →
Downloads · 30-day
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Model age
today
created 2026-10-21

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Languages
en it zh
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf qwen3_5 qwopus abliterated uncensored Claude reasoning chain-of-thought conversational en it

Related

Total size
174 GB
Files
13
Quantizations
8
Registered
2026-10-21 08:00
Last updated on HF
2026-10-21 06:47

Files by quantization

Q8_0 1 file 26.6 GB
Qwopus3.5-27B-v3-Abliterated.Q8_0.gguf 26.6 GB 8d79bcb5 download
Q6_K 1 file 20.6 GB
Qwopus3.5-27B-v3-Abliterated.Q6_K.gguf 20.6 GB ed6e2c7e download
Q5_K 2 files 35.3 GB
Qwopus3.5-27B-v3-Abliterated.Q5_K_M.gguf 17.9 GB 60d451d7 download
Qwopus3.5-27B-v3-Abliterated.Q5_K_S.gguf 17.4 GB 9163e0ff download
Q4_K 2 files 29.9 GB
Qwopus3.5-27B-v3-Abliterated.Q4_K_M.gguf 15.4 GB 79e7aa6f download
Qwopus3.5-27B-v3-Abliterated.Q4_K_S.gguf 14.5 GB ed177961 download
IQ4 1 file 14.2 GB
Qwopus3.5-27B-v3-Abliterated.IQ4_XS.gguf 14.2 GB 1d59d530 download
Q3_K 3 files 37.0 GB
Qwopus3.5-27B-v3-Abliterated.Q3_K_L.gguf 13.4 GB 38e67b21 download
Qwopus3.5-27B-v3-Abliterated.Q3_K_M.gguf 12.4 GB 1958a07f download
Qwopus3.5-27B-v3-Abliterated.Q3_K_S.gguf 11.2 GB e21d754a download
Q2_K 1 file 9.98 GB
Qwopus3.5-27B-v3-Abliterated.Q2_K.gguf 9.98 GB f0fe61d1 download
Auxiliary files 2 files 6.37 KB
README.md 4.07 KB 2e1ce109 download
.gitattributes 2.30 KB 8ee15a54 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

static 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.

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 Q2_K 10.8
GGUF Q3_K_S 12.2
GGUF Q3_K_M 13.4 lower quality
GGUF Q3_K_L 14.4
GGUF IQ4_XS 15.3
GGUF Q4_K_S 15.7 fast, recommended
GGUF Q4_K_M 16.6 fast, recommended
GGUF Q5_K_S 18.8
GGUF Q5_K_M 19.3
GGUF Q6_K 22.2 very good quality
GGUF Q8_0 28.7 fast, best quality

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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