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

mradermacher/gemma-2-2b-ORPO-jpn-it-abliterated-18-i1-GGUF

mradermacher Gemma 2B GGUF second-order 8K ctx
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Response includes
  • classification m8
  • files 27
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  • author_summary 3324 models
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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='ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

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Downloads · lifetime
5K
626 last 30d - stable
Likes
0
Model age
23mo ago
created 2024-10-31

Training datasets

1 of 1 in /datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now4.9K→from468↑944%
01.8K3.6K5.4K468 on Oct 30, 20244.9K on Oct 114.9K on Oct 10Oct '24Feb '25Jun '25Oct '25FebJunOct
Oct 30, 2024 → Oct 11 · 141 snapshots · spans 711 days

Genealogy 0 direct forks

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Variants by this author 2 formats · 931 downloads combined

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

Metadata

License
gemma
Languages
multilingual
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf nlp code multilingual dataset:mlabonne/orpo-dpo-mix-40k base_model:ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18 base_model:quantized:ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18 license:gemma endpoints_compatible region:us imatrix

Related

Total size
31.7 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2024-11-02 14:51

Files by quantization

Q6_K 1 file 2.00 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q6_K.gguf 2.00 GB 61dca0ed download
Q5_K 2 files 3.54 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q5_K_M.gguf 1.79 GB 6bc24d45 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q5_K_S.gguf 1.75 GB 1c0de342 download
Q4_K 2 files 3.12 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_K_M.gguf 1.59 GB abbe9019 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_K_S.gguf 1.53 GB a3e8b71b download
Q4 4 files 6.07 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_0.gguf 1.52 GB d37e4e82 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_0_4_4.gguf 1.52 GB 796df8cb download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_0_4_8.gguf 1.52 GB 06078357 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q4_0_8_8.gguf 1.52 GB 3ce17abb download
IQ4 1 file 1.46 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ4_XS.gguf 1.46 GB ad9c1e55 download
Q3_K 3 files 4.07 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q3_K_L.gguf 1.44 GB fc712a74 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q3_K_M.gguf 1.36 GB bf000b57 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q3_K_S.gguf 1.27 GB b575b8e6 download
IQ3 4 files 4.89 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ3_M.gguf 1.30 GB 1c9114d8 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ3_S.gguf 1.27 GB 90cf8941 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ3_XS.gguf 1.22 GB a810afda download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ3_XXS.gguf 1.10 GB 6cd81321 download
Q2_K 1 file 1.15 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-Q2_K.gguf 1.15 GB ff2c32a4 download
IQ2 4 files 3.79 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ2_M.gguf 1.01 GB 64b16e08 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ2_S.gguf 985 MB 92014ec2 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ2_XS.gguf 956 MB d008d3b6 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ2_XXS.gguf 900 MB 3a63055e download
IQ1 2 files 1.59 GB
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ1_M.gguf 833 MB 3bab4617 download
gemma-2-2b-ORPO-jpn-it-abliterated-18.i1-IQ1_S.gguf 794 MB 86d965a4 download
Auxiliary files 3 files 2.28 MB
imatrix.dat 2.27 MB 3f8e7a82 download
README.md 6.45 KB c541b5ba download
.gitattributes 3.61 KB b3d8ce29 download

README current version from Hugging Face


base_model: ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18
datasets:

  • mlabonne/orpo-dpo-mix-40k
    language:
  • multilingual
    library_name: transformers
    license: gemma
    license_link: https://ai.google.dev/gemma/terms
    quantized_by: mradermacher
    tags:
  • nlp
  • code

About

weighted/imatrix quants of https://huggingface.co/ymcki/gemma-2-2b-ORPO-jpn-it-abliterated-18

static quants are available at https://huggingface.co/mradermacher/gemma-2-2b-ORPO-jpn-it-abliterated-18-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 i1-IQ1_S 0.9 for the desperate
GGUF i1-IQ1_M 1.0 mostly desperate
GGUF i1-IQ2_XXS 1.0
GGUF i1-IQ2_XS 1.1
GGUF i1-IQ2_S 1.1
GGUF i1-IQ2_M 1.2
GGUF i1-IQ3_XXS 1.3 lower quality
GGUF i1-Q2_K 1.3 IQ3_XXS probably better
GGUF i1-IQ3_XS 1.4
GGUF i1-IQ3_S 1.5 beats Q3_K*
GGUF i1-Q3_K_S 1.5 IQ3_XS probably better
GGUF i1-IQ3_M 1.5
GGUF i1-Q3_K_M 1.6 IQ3_S probably better
GGUF i1-Q3_K_L 1.7 IQ3_M probably better
GGUF i1-IQ4_XS 1.7
GGUF i1-Q4_0_4_4 1.7 fast on arm, low quality
GGUF i1-Q4_0_4_8 1.7 fast on arm+i8mm, low quality
GGUF i1-Q4_0_8_8 1.7 fast on arm+sve, low quality
GGUF i1-Q4_0 1.7 fast, low quality
GGUF i1-Q4_K_S 1.7 optimal size/speed/quality
GGUF i1-Q4_K_M 1.8 fast, recommended
GGUF i1-Q5_K_S 2.0
GGUF i1-Q5_K_M 2.0
GGUF i1-Q6_K 2.3 practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

README history 3 versions

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

  1. 2024-11-02auto-patch README.md4baf8ec6.4 KB
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  2. 2024-10-31auto-patch README.md0cfd1d16.5 KB
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  3. 2024-10-31uploaded from nethype/db33d39037251 B
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