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

mradermacher/Laguna-S-2.1-Uncensored-GGUF

mradermacher GGUF MoE second-order 1.0M ctx
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Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 1,638
  • 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='SC117/Laguna-S-2.1-Uncensored' (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.

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Downloads · lifetime
2K
747 last 30d - stable
Likes
0
Model age
2mo ago
created 2026-08-03
Downloads over time
Now2.1K→from650↑220%
5781.1K1.7K2.2K650 on Aug 52.1K on Oct 11AugSepOct
Aug 5 → Oct 11 · 51 snapshots · spans 67 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

License
other
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K
Tags
transformers gguf laguna moe uncensored abliterix safetensors bf16 poolside en base_model:SC117/Laguna-S-2.1-Uncensored base_model:quantized:SC117/Laguna-S-2.1-Uncensored

Related

Total size
627 GB
Files
15
Quantizations
7
Registered
2026-08-22 13:56
Last updated on HF
2026-08-03 14:49

Files by quantization

Q6_K 1 file 89.9 GB
Laguna-S-2.1-Uncensored.Q6_K.gguf 89.9 GB c4d98407 download
Q5_K 2 files 153 GB
Laguna-S-2.1-Uncensored.Q5_K_M.gguf 77.7 GB 3ed41fc5 download
Laguna-S-2.1-Uncensored.Q5_K_S.gguf 75.4 GB 0a4b4e19 download
Q4_K 2 files 129 GB
Laguna-S-2.1-Uncensored.Q4_K_M.gguf 66.3 GB 060e7157 download
Laguna-S-2.1-Uncensored.Q4_K_S.gguf 62.3 GB c0f7c243 download
IQ4 1 file 59.0 GB
Laguna-S-2.1-Uncensored.IQ4_XS.gguf 59.0 GB d5157e76 download
Q3_K 3 files 156 GB
Laguna-S-2.1-Uncensored.Q3_K_L.gguf 56.8 GB 76462b0b download
Laguna-S-2.1-Uncensored.Q3_K_M.gguf 52.4 GB 0d7cf691 download
Laguna-S-2.1-Uncensored.Q3_K_S.gguf 47.3 GB 4deabc2f download
Q2_K 1 file 39.9 GB
Laguna-S-2.1-Uncensored.Q2_K.gguf 39.9 GB 606bb467 download
Auxiliary files 5 files 116 GB
Laguna-S-2.1-Uncensored.Q8_0.gguf.part1of3 39.0 GB af2ab4ad download
Laguna-S-2.1-Uncensored.Q8_0.gguf.part2of3 39.0 GB 882feabe download
Laguna-S-2.1-Uncensored.Q8_0.gguf.part3of3 38.4 GB 9d9d0750 download
README.md 3.88 KB 6ae4a288 download
.gitattributes 2.41 KB 76ccd7d1 download

README current version from Hugging Face


base_model: SC117/Laguna-S-2.1-Uncensored
language:

  • en
    library_name: transformers
    license: other
    license_link: https://openmdw.ai/
    license_name: openmdw-1.1
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • laguna
  • moe
  • uncensored
  • abliterix
  • safetensors
  • bf16
  • poolside

About

static quants of https://huggingface.co/SC117/Laguna-S-2.1-Uncensored

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Laguna-S-2.1-Uncensored-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 43.0
GGUF Q3_K_S 50.9
GGUF Q3_K_M 56.3 lower quality
GGUF Q3_K_L 61.0
GGUF IQ4_XS 63.4
GGUF Q4_K_S 67.0 fast, recommended
GGUF Q4_K_M 71.3 fast, recommended
GGUF Q5_K_S 81.1
GGUF Q5_K_M 83.6
GGUF Q6_K 96.7 very good quality
PART 1 PART 2 PART 3 Q8_0 125.1 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 10 versions

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

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  10. 2026-08-03uploaded from rich1188cf0a372 B
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