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

mradermacher/sarashina2-7b-abliterated-GGUF

mradermacher 7B GGUF second-order 4K ctx
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Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 1,747
  • 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='ronantakizawa/sarashina2-7b-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
231 last 30d - stable
Likes
0
Model age
11mo ago
created 2025-10-24
Downloads over time
Now1.8K→from243↑655%
1637741.4K2K243 on Oct 22, 20251.8K on Oct 11Oct '25Dec '25FebAprJunAugOct
Oct 22, 2025 → Oct 11 · 90 snapshots · spans 354 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 · 1K downloads combined

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

Metadata

License
mit
Languages
ja en
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliteration uncensored refusal-removal japanese ja en base_model:ronantakizawa/sarashina2-7b-abliterated base_model:quantized:ronantakizawa/sarashina2-7b-abliterated license:mit endpoints_compatible

Related

Total size
60.8 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-10-24 12:44

Files by quantization

F16 1 file 13.6 GB
sarashina2-7b-abliterated.f16.gguf 13.6 GB ae32d14a download
Q8_0 1 file 7.24 GB
sarashina2-7b-abliterated.Q8_0.gguf 7.24 GB abc99cda download
Q6_K 1 file 5.59 GB
sarashina2-7b-abliterated.Q6_K.gguf 5.59 GB 112cb042 download
Q5_K 2 files 9.60 GB
sarashina2-7b-abliterated.Q5_K_M.gguf 4.86 GB 47f28084 download
sarashina2-7b-abliterated.Q5_K_S.gguf 4.74 GB b9ee7500 download
Q4_K 2 files 8.14 GB
sarashina2-7b-abliterated.Q4_K_M.gguf 4.17 GB 6c312d8e download
sarashina2-7b-abliterated.Q4_K_S.gguf 3.96 GB fb2c68b3 download
IQ4 1 file 3.76 GB
sarashina2-7b-abliterated.IQ4_XS.gguf 3.76 GB b3d83903 download
Q3_K 3 files 10.2 GB
sarashina2-7b-abliterated.Q3_K_L.gguf 3.69 GB bd1e208d download
sarashina2-7b-abliterated.Q3_K_M.gguf 3.41 GB c059b0f8 download
sarashina2-7b-abliterated.Q3_K_S.gguf 3.08 GB 3a74fa69 download
Q2_K 1 file 2.67 GB
sarashina2-7b-abliterated.Q2_K.gguf 2.67 GB 5ff240fc download
Auxiliary files 2 files 6.09 KB
README.md 3.75 KB f2d1f6cd download
.gitattributes 2.34 KB d5da6ca2 download

README current version from Hugging Face


base_model: ronantakizawa/sarashina2-7b-abliterated
language:

  • ja
  • en
    library_name: transformers
    license: mit
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliteration
  • uncensored
  • refusal-removal
  • japanese

About

static quants of https://huggingface.co/ronantakizawa/sarashina2-7b-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/sarashina2-7b-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 3.0
GGUF Q3_K_S 3.4
GGUF Q3_K_M 3.8 lower quality
GGUF Q3_K_L 4.1
GGUF IQ4_XS 4.1
GGUF Q4_K_S 4.4 fast, recommended
GGUF Q4_K_M 4.6 fast, recommended
GGUF Q5_K_S 5.2
GGUF Q5_K_M 5.3
GGUF Q6_K 6.1 very good quality
GGUF Q8_0 7.9 fast, best quality
GGUF f16 14.7 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 4 versions

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

  1. 2025-10-24auto-patch README.md72655043.8 KB
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  2. 2025-10-24auto-patch README.md23b45a03.9 KB
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  3. 2025-10-24auto-patch README.md42a59b43.7 KB
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  4. 2025-10-24uploaded from marco2c8c9a6382 B
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