← back to catalog · registered 2026-10-30 11:01

mradermacher/Granite-4.2-8B-Surgical-Abliterated-GGUF

mradermacher 8B GGUF second-order
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FGranite-4.2-8B-Surgical-Abliterated-GGUF"
Response includes
  • classification m8
  • files 14
  • author_summary 3427 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='medismera/Granite-4.2-8B-Surgical-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
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Model age
today
created 2026-10-30

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored surgical-alignment causal-lm safetensors en base_model:medismera/Granite-4.2-8B-Surgical-Abliterated base_model:quantized:medismera/Granite-4.2-8B-Surgical-Abliterated license:apache-2.0 endpoints_compatible

Related

Total size
72.8 GB
Files
14
Quantizations
9
Registered
2026-10-30 11:01
Last updated on HF
2026-10-30 11:26

Files by quantization

F16 1 file 16.4 GB
Granite-4.2-8B-Surgical-Abliterated.f16.gguf 16.4 GB 877853b8 download
Q8_0 1 file 8.70 GB
Granite-4.2-8B-Surgical-Abliterated.Q8_0.gguf 8.70 GB 9289dfe6 download
Q6_K 1 file 6.72 GB
Granite-4.2-8B-Surgical-Abliterated.Q6_K.gguf 6.72 GB 9264448e download
Q5_K 2 files 11.5 GB
Granite-4.2-8B-Surgical-Abliterated.Q5_K_M.gguf 5.82 GB 9e05d4cb download
Granite-4.2-8B-Surgical-Abliterated.Q5_K_S.gguf 5.68 GB a9e9c1c3 download
Q4_K 2 files 9.72 GB
Granite-4.2-8B-Surgical-Abliterated.Q4_K_M.gguf 4.98 GB c2ba20a5 download
Granite-4.2-8B-Surgical-Abliterated.Q4_K_S.gguf 4.74 GB d9a39b4c download
IQ4 1 file 4.53 GB
Granite-4.2-8B-Surgical-Abliterated.IQ4_XS.gguf 4.53 GB e1bf0547 download
Q3_K 3 files 12.1 GB
Granite-4.2-8B-Surgical-Abliterated.Q3_K_L.gguf 4.38 GB f8b74242 download
Granite-4.2-8B-Surgical-Abliterated.Q3_K_M.gguf 4.05 GB 2e271d8f download
Granite-4.2-8B-Surgical-Abliterated.Q3_K_S.gguf 3.67 GB 770d3298 download
Q2_K 1 file 3.18 GB
Granite-4.2-8B-Surgical-Abliterated.Q2_K.gguf 3.18 GB 6ab84342 download
Auxiliary files 2 files 6.44 KB
README.md 3.98 KB 5e981407 download
.gitattributes 2.46 KB f74f1606 download

README current version from Hugging Face


base_model: medismera/Granite-4.2-8B-Surgical-Abliterated
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • surgical-alignment
  • causal-lm
  • safetensors

About

static quants of https://huggingface.co/medismera/Granite-4.2-8B-Surgical-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 3.5
GGUF Q3_K_S 4.0
GGUF Q3_K_M 4.4 lower quality
GGUF Q3_K_L 4.8
GGUF Q4_K_S 5.2 fast, recommended
GGUF Q4_K_M 5.4 fast, recommended
GGUF Q5_K_S 6.2
GGUF Q5_K_M 6.4
GGUF Q6_K 7.3 very good quality
GGUF Q8_0 9.4 fast, best quality
GGUF f16 17.7 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.

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