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mradermacher/gemma-3-1b-it-abliterated-v2-GGUF

mradermacher Gemma 1B GGUF second-order 33K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2Fgemma-3-1b-it-abliterated-v2-GGUF"
Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 2,039
  • 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='mlabonne/gemma-3-1b-it-abliterated-v2' (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
423 last 30d - stable
Likes
0
Model age
16mo ago
created 2025-05-29
Downloads over time
Now2.3K→from192↑1,076%
898811.7K2.5K192 on May 28, 20252.3K on Oct 11May '25Aug '25Nov '25FebMayAug
May 28, 2025 → Oct 11 · 111 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.

Metadata

License
gemma
Languages
en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf en base_model:mlabonne/gemma-3-1b-it-abliterated-v2 base_model:quantized:mlabonne/gemma-3-1b-it-abliterated-v2 license:gemma endpoints_compatible region:us conversational

Related

Total size
10.2 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-05-29 11:16

Files by quantization

F16 1 file 1.87 GB
gemma-3-1b-it-abliterated-v2.f16.gguf 1.87 GB 13805bba download
Q8_0 1 file 1020 MB
gemma-3-1b-it-abliterated-v2.Q8_0.gguf 1020 MB 6e045835 download
Q6_K 1 file 965 MB
gemma-3-1b-it-abliterated-v2.Q6_K.gguf 965 MB c84b4003 download
Q5_K 2 files 1.57 GB
gemma-3-1b-it-abliterated-v2.Q5_K_M.gguf 812 MB 4c59fc9c download
gemma-3-1b-it-abliterated-v2.Q5_K_S.gguf 798 MB dc11bae5 download
Q4_K 2 files 1.48 GB
gemma-3-1b-it-abliterated-v2.Q4_K_M.gguf 769 MB c3c5a622 download
gemma-3-1b-it-abliterated-v2.Q4_K_S.gguf 745 MB 4349daf1 download
Q3_K 3 files 2.01 GB
gemma-3-1b-it-abliterated-v2.Q3_K_L.gguf 717 MB e68de7ad download
gemma-3-1b-it-abliterated-v2.Q3_K_M.gguf 689 MB e9677fd3 download
gemma-3-1b-it-abliterated-v2.Q3_K_S.gguf 657 MB e100e267 download
IQ4 1 file 685 MB
gemma-3-1b-it-abliterated-v2.IQ4_XS.gguf 685 MB 0b572d95 download
Q2_K 1 file 658 MB
gemma-3-1b-it-abliterated-v2.Q2_K.gguf 658 MB 92f97417 download
Auxiliary files 2 files 5.92 KB
README.md 3.55 KB 85d35f39 download
.gitattributes 2.38 KB 5e360955 download

README current version from Hugging Face


base_model: mlabonne/gemma-3-1b-it-abliterated-v2
language:

  • en
    library_name: transformers
    license: gemma
    quantized_by: mradermacher

About

static quants of https://huggingface.co/mlabonne/gemma-3-1b-it-abliterated-v2

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 Q3_K_S 0.8
GGUF Q2_K 0.8
GGUF IQ4_XS 0.8
GGUF Q3_K_M 0.8 lower quality
GGUF Q3_K_L 0.9
GGUF Q4_K_S 0.9 fast, recommended
GGUF Q4_K_M 0.9 fast, recommended
GGUF Q5_K_S 0.9
GGUF Q5_K_M 1.0
GGUF Q6_K 1.1 very good quality
GGUF Q8_0 1.2 fast, best quality
GGUF f16 2.1 16 bpw, overkill

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 2 versions

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

  1. 2025-05-29auto-patch README.mdf779f2b3.5 KB
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  2. 2025-05-29uploaded from leiab9ec492227 B
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Discussions 1 thread

  1. 2025-08-04IQ4_NLclosed3 💬#1
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