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mradermacher/EXAONE-3.5-32B-Instruct-abliterated-GGUF

mradermacher 32B GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 3,816
  • 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 layer-wise ablation 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='huihui-ai/EXAONE-3.5-32B-Instruct-abliterated' (base is huihui-ai model (M3))
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 · lifetime
4K
261 last 30d - cooling
Likes
0
Model age
21mo ago
created 2024-12-20
Downloads over time
Now3.9K→from240↑1,518%
01.4K2.8K4.3K240 on Dec 18, 20243.9K on Oct 113.9K on Oct 10Dec '24Mar '25Jun '25Sep '25Dec '25MarJunSep
Dec 18, 2024 → Oct 11 · 134 snapshots · spans 662 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 · 692 downloads combined

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

Metadata

License
other
Languages
en ko
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf lg-ai exaone exaone-3.5 abliterated uncensored en ko license:other endpoints_compatible region:us

Related

Total size
203 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2025-08-01 00:13

Files by quantization

Q8_0 1 file 31.7 GB
EXAONE-3.5-32B-Instruct-abliterated.Q8_0.gguf 31.7 GB 90404389 download
Q6_K 1 file 24.5 GB
EXAONE-3.5-32B-Instruct-abliterated.Q6_K.gguf 24.5 GB 8b35ce38 download
Q5_K 2 files 41.7 GB
EXAONE-3.5-32B-Instruct-abliterated.Q5_K_M.gguf 21.1 GB 790b2af7 download
EXAONE-3.5-32B-Instruct-abliterated.Q5_K_S.gguf 20.6 GB 3739e670 download
Q4_K 2 files 35.0 GB
EXAONE-3.5-32B-Instruct-abliterated.Q4_K_M.gguf 18.0 GB 9d6ee794 download
EXAONE-3.5-32B-Instruct-abliterated.Q4_K_S.gguf 17.0 GB fe3a6f42 download
IQ4 1 file 16.2 GB
EXAONE-3.5-32B-Instruct-abliterated.IQ4_XS.gguf 16.2 GB 33705734 download
Q3_K 3 files 43.1 GB
EXAONE-3.5-32B-Instruct-abliterated.Q3_K_L.gguf 15.6 GB b93dfa18 download
EXAONE-3.5-32B-Instruct-abliterated.Q3_K_M.gguf 14.4 GB 5bfa4b30 download
EXAONE-3.5-32B-Instruct-abliterated.Q3_K_S.gguf 13.0 GB 23cd1986 download
Q2_K 1 file 11.1 GB
EXAONE-3.5-32B-Instruct-abliterated.Q2_K.gguf 11.1 GB 67fc6be0 download
Auxiliary files 2 files 6.13 KB
README.md 3.75 KB df92fcff download
.gitattributes 2.38 KB ca1fa798 download

README current version from Hugging Face


base_model: huihui-ai/EXAONE-3.5-32B-Instruct-abliterated
language:

  • en
  • ko
    library_name: transformers
    license: other
    license_link: LICENSE
    license_name: exaone
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • lg-ai
  • exaone
  • exaone-3.5
  • abliterated
  • uncensored

About

static quants of https://huggingface.co/huihui-ai/EXAONE-3.5-32B-Instruct-abliterated

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/EXAONE-3.5-32B-Instruct-abliterated-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 Q2_K 12.0
GGUF Q3_K_S 14.1
GGUF Q3_K_M 15.6 lower quality
GGUF Q3_K_L 16.9
GGUF IQ4_XS 17.5
GGUF Q4_K_S 18.4 fast, recommended
GGUF Q4_K_M 19.4 fast, recommended
GGUF Q5_K_S 22.2
GGUF Q5_K_M 22.8
GGUF Q6_K 26.4 very good quality
GGUF Q8_0 34.1 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.

README history 4 versions

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

  1. 2025-08-01auto-patch README.md65478453.7 KB
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  2. 2024-12-21auto-patch README.mdb04f2b83.8 KB
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  3. 2024-12-21auto-patch README.mdfcdca643.2 KB
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  4. 2024-12-20uploaded from nico18568158235 B
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