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mradermacher/medgemma-27b-abliterated-multimodal-GGUF

mradermacher 27B GGUF second-order 131K ctx
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Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 11,732
  • 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='ToastyPigeon/medgemma-27b-abliterated-multimodal' (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
12K
1K last 30d - cooling
Likes
5
Model age
16mo ago
created 2025-06-01
Downloads over time
Now12K→from185↑6,368%
04.4K8.8K13.2K185 on May 28, 202512K on Oct 11May '25Aug '25Nov '25FebMayAug
May 28, 2025 → Oct 11 · 114 snapshots · spans 501 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 · 2K 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 Q5_K Q6_K Q8_0
Tags
transformers gguf en endpoints_compatible region:us conversational

Related

Total size
174 GB
Files
15
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-08-01 06:53

Files by quantization

Q8_0 2 files 27.3 GB
medgemma-27b-abliterated-multimodal.Q8_0.gguf 26.7 GB 5d5510be download
medgemma-27b-abliterated-multimodal.mmproj-Q8_0.gguf 570 MB 024390d9 download
Q6_K 1 file 20.6 GB
medgemma-27b-abliterated-multimodal.Q6_K.gguf 20.6 GB bd970ccb download
Q5_K 2 files 35.4 GB
medgemma-27b-abliterated-multimodal.Q5_K_M.gguf 17.9 GB 83135c4e download
medgemma-27b-abliterated-multimodal.Q5_K_S.gguf 17.5 GB 1d7f6856 download
Q4_K 2 files 30.0 GB
medgemma-27b-abliterated-multimodal.Q4_K_M.gguf 15.4 GB 52240053 download
medgemma-27b-abliterated-multimodal.Q4_K_S.gguf 14.6 GB 463e4cac download
IQ4 1 file 13.9 GB
medgemma-27b-abliterated-multimodal.IQ4_XS.gguf 13.9 GB 1b909fd7 download
Q3_K 3 files 37.4 GB
medgemma-27b-abliterated-multimodal.Q3_K_L.gguf 13.5 GB 46bc7ec7 download
medgemma-27b-abliterated-multimodal.Q3_K_M.gguf 12.5 GB 5f5e0866 download
medgemma-27b-abliterated-multimodal.Q3_K_S.gguf 11.3 GB b58b8e29 download
Q2_K 1 file 9.78 GB
medgemma-27b-abliterated-multimodal.Q2_K.gguf 9.78 GB c5c4fca7 download
F16 1 file 818 MB
medgemma-27b-abliterated-multimodal.mmproj-f16.gguf 818 MB b0684b22 download
Auxiliary files 2 files 6.57 KB
README.md 4.02 KB b37a6ef0 download
.gitattributes 2.55 KB 6889f81a download

README current version from Hugging Face


base_model: ToastyPigeon/medgemma-27b-abliterated-multimodal
language:

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

About

static quants of https://huggingface.co/ToastyPigeon/medgemma-27b-abliterated-multimodal

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/medgemma-27b-abliterated-multimodal-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 0.7 multi-modal supplement
GGUF mmproj-f16 1.0 multi-modal supplement
GGUF Q2_K 10.6
GGUF Q3_K_S 12.3
GGUF Q3_K_M 13.5 lower quality
GGUF Q3_K_L 14.6
GGUF IQ4_XS 15.0
GGUF Q4_K_S 15.8 fast, recommended
GGUF Q4_K_M 16.6 fast, recommended
GGUF Q5_K_S 18.9
GGUF Q5_K_M 19.4
GGUF Q6_K 22.3 very good quality
GGUF Q8_0 28.8 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 5 versions

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

  1. 2025-08-01auto-patch README.mdad3ffe74 KB
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  2. 2025-07-11auto-patch README.md64efce84.2 KB
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  3. 2025-06-02auto-patch README.mdf3cdd833.7 KB
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  4. 2025-06-01auto-patch README.md4ac0f553.1 KB
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  5. 2025-06-01uploaded from nico16d2b12a238 B
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