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mradermacher/Muse-Glimmer-30B-Abliterated-GGUF

mradermacher 30B GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 1,971
  • 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='jorkle/Muse-Glimmer-30B-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
2K
1K last 30d - active
Likes
0
Model age
8w ago
created 2026-08-13
Downloads over time
Now2.4K→from1.2K↑104%
1.1K1.6K2K2.5K1.2K on Aug 192.4K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 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 4 formats · 4K 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
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated muse-glimmer lora de-refusal en base_model:jorkle/Muse-Glimmer-30B-Abliterated base_model:adapter:jorkle/Muse-Glimmer-30B-Abliterated license:apache-2.0 endpoints_compatible region:us

Related

Total size
178 GB
Files
15
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2026-10-07 12:53

Files by quantization

Q8_0 2 files 29.5 GB
Muse-Glimmer-30B-Abliterated.Q8_0.gguf 27.6 GB fcd4fe2d download
Muse-Glimmer-30B-Abliterated.mmproj-Q8_0.gguf 1.91 GB 26f31e60 download
Q6_K 1 file 21.3 GB
Muse-Glimmer-30B-Abliterated.Q6_K.gguf 21.3 GB a148ddb8 download
Q5_K 2 files 36.5 GB
Muse-Glimmer-30B-Abliterated.Q5_K_M.gguf 18.5 GB 1f7e7510 download
Muse-Glimmer-30B-Abliterated.Q5_K_S.gguf 18.0 GB b78b55f6 download
Q4_K 2 files 30.8 GB
Muse-Glimmer-30B-Abliterated.Q4_K_M.gguf 15.8 GB 48e4de5a download
Muse-Glimmer-30B-Abliterated.Q4_K_S.gguf 15.0 GB 0e1fab6d download
IQ4 1 file 14.3 GB
Muse-Glimmer-30B-Abliterated.IQ4_XS.gguf 14.3 GB bd7005d7 download
Q3_K 3 files 38.1 GB
Muse-Glimmer-30B-Abliterated.Q3_K_L.gguf 13.7 GB e7d36985 download
Muse-Glimmer-30B-Abliterated.Q3_K_M.gguf 12.7 GB 6baa9d90 download
Muse-Glimmer-30B-Abliterated.Q3_K_S.gguf 11.7 GB e393c800 download
Q2_K 1 file 9.95 GB
Muse-Glimmer-30B-Abliterated.Q2_K.gguf 9.95 GB 85149452 download
F16 1 file 3.58 GB
Muse-Glimmer-30B-Abliterated.mmproj-f16.gguf 3.58 GB 4f71e778 download
Auxiliary files 2 files 6.49 KB
README.md 4.03 KB 6552c620 download
.gitattributes 2.46 KB 6d151dbc download

README current version from Hugging Face


base_model: jorkle/Muse-Glimmer-30B-Abliterated
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • muse-glimmer
  • lora
  • de-refusal

About

static quants of https://huggingface.co/jorkle/Muse-Glimmer-30B-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/Muse-Glimmer-30B-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 mmproj-Q8_0 2.2 multi-modal supplement
GGUF mmproj-f16 3.9 multi-modal supplement
GGUF Q2_K 10.8
GGUF Q3_K_S 12.6
GGUF Q3_K_M 13.8 lower quality
GGUF Q3_K_L 14.8
GGUF IQ4_XS 15.4
GGUF Q4_K_S 16.2 fast, recommended
GGUF Q4_K_M 17.0 fast, recommended
GGUF Q5_K_S 19.4
GGUF Q5_K_M 19.9
GGUF Q6_K 23.0 very good quality
GGUF Q8_0 29.7 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.

README history 8 versions

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

  1. 2026-10-07auto-patch README.md3cb06304.2 KB
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  2. 2026-08-13auto-patch README.mdfee0f374 KB
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  3. 2026-08-13auto-patch README.md5f5ab2d4.1 KB
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  4. 2026-08-13auto-patch README.mda03e7614 KB
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  5. 2026-08-13auto-patch README.md5b1db823.7 KB
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  6. 2026-08-13auto-patch README.mdad1db873.5 KB
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  7. 2026-08-13auto-patch README.mdf1907682.6 KB
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  8. 2026-08-13uploaded from nico1531457d378 B
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