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

mradermacher/A.X-4.0-abliterated-GGUF

mradermacher GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 17
  • hub_downloads_all_time 474
  • 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='nicoboss/A.X-4.0-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 · lifetime
474
225 last 30d - stable
Likes
0
Model age
14mo ago
created 2025-08-03
Downloads over time
Now585→from57↑926%
3123343563857 on Aug 6, 2025585 on Oct 11Aug '25Oct '25Dec '25FebAprJunAugOct
Aug 6, 2025 → Oct 11 · 101 snapshots · spans 431 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 · 653 downloads combined

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

Metadata

Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K
Tags
transformers gguf en base_model:nicoboss/A.X-4.0-abliterated base_model:quantized:nicoboss/A.X-4.0-abliterated endpoints_compatible region:us conversational

Related

Total size
251 GB
Files
17
Quantizations
5
Registered
2026-08-22 13:56
Last updated on HF
2025-08-03 19:30

Files by quantization

Q4_K 2 files 84.0 GB
A.X-4.0-abliterated.Q4_K_M.gguf 43.6 GB 12f72f5e download
A.X-4.0-abliterated.Q4_K_S.gguf 40.4 GB 64e01f05 download
IQ4 1 file 36.9 GB
A.X-4.0-abliterated.IQ4_XS.gguf 36.9 GB 629e860b download
Q3_K 3 files 103 GB
A.X-4.0-abliterated.Q3_K_L.gguf 36.3 GB edf75f80 download
A.X-4.0-abliterated.Q3_K_M.gguf 34.6 GB 154854ad download
A.X-4.0-abliterated.Q3_K_S.gguf 31.6 GB 3aca5f49 download
Q2_K 1 file 27.3 GB
A.X-4.0-abliterated.Q2_K.gguf 27.3 GB b1c6b1cc download
Auxiliary files 10 files 228 GB
A.X-4.0-abliterated.Q8_0.gguf.part1of2 36.0 GB d56729d8 download
A.X-4.0-abliterated.Q8_0.gguf.part2of2 35.2 GB 58ff942e download
A.X-4.0-abliterated.Q6_K.gguf.part1of2 30.0 GB cddd00c3 download
A.X-4.0-abliterated.Q6_K.gguf.part2of2 29.3 GB 401d6a90 download
A.X-4.0-abliterated.Q5_K_M.gguf.part1of2 26.0 GB 56d1bca2 download
A.X-4.0-abliterated.Q5_K_M.gguf.part2of2 24.1 GB 5c1f94fe download
A.X-4.0-abliterated.Q5_K_S.gguf.part1of2 24.0 GB b063f877 download
A.X-4.0-abliterated.Q5_K_S.gguf.part2of2 23.3 GB 7acbb7c3 download
README.md 3.89 KB 218faab0 download
.gitattributes 2.54 KB 4f009445 download

README current version from Hugging Face


base_model: nicoboss/A.X-4.0-abliterated
language:

  • en
    library_name: transformers
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher

About

static quants of https://huggingface.co/nicoboss/A.X-4.0-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/A.X-4.0-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 29.4
GGUF Q3_K_S 34.1
GGUF Q3_K_M 37.3 lower quality
GGUF Q3_K_L 39.1
GGUF IQ4_XS 39.7
GGUF Q4_K_S 43.4 fast, recommended
GGUF Q4_K_M 47.0 fast, recommended
PART 1 PART 2 Q5_K_S 50.9
PART 1 PART 2 Q5_K_M 53.9
PART 1 PART 2 Q6_K 63.8 very good quality
PART 1 PART 2 Q8_0 76.5 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 3 versions

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

  1. 2025-08-03auto-patch README.mdd1046293.9 KB
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  2. 2025-08-03auto-patch README.md514f5893.6 KB
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  3. 2025-08-03uploaded from nico1af46e61370 B
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