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mradermacher/Huihui-SmolLM3-3B-abliterated-GGUF

mradermacher 3B GGUF second-order 66K ctx
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Response includes
  • classification m8
  • files 14
  • hub_downloads_all_time 3,122
  • 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 layer-wise ablation 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='huihui-ai/Huihui-SmolLM3-3B-abliterated' (base is huihui-ai model (M3))
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
3K
644 last 30d - stable
Likes
1
Model age
15mo ago
created 2025-07-15
Downloads over time
Now3.3K→from269↑1,141%
1161.3K2.5K3.6K269 on Jul 16, 20253.3K on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 16, 2025 → Oct 11 · 104 snapshots · spans 452 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
apache-2.0
Languages
en fr es it pt zh ar ru
Quantizations
F16 IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored en fr es it pt zh ar ru

Related

Total size
25.8 GB
Files
14
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-07-15 23:00

Files by quantization

F16 1 file 5.74 GB
Huihui-SmolLM3-3B-abliterated.f16.gguf 5.74 GB 54f31897 download
Q8_0 1 file 3.05 GB
Huihui-SmolLM3-3B-abliterated.Q8_0.gguf 3.05 GB 091c9cc4 download
Q6_K 1 file 2.36 GB
Huihui-SmolLM3-3B-abliterated.Q6_K.gguf 2.36 GB ef94757a download
Q5_K 2 files 4.07 GB
Huihui-SmolLM3-3B-abliterated.Q5_K_M.gguf 2.06 GB 8b847734 download
Huihui-SmolLM3-3B-abliterated.Q5_K_S.gguf 2.01 GB 276b51b7 download
Q4_K 2 files 3.48 GB
Huihui-SmolLM3-3B-abliterated.Q4_K_M.gguf 1.78 GB d3ce3171 download
Huihui-SmolLM3-3B-abliterated.Q4_K_S.gguf 1.69 GB b64987f7 download
IQ4 1 file 1.62 GB
Huihui-SmolLM3-3B-abliterated.IQ4_XS.gguf 1.62 GB b3d7fe04 download
Q3_K 3 files 4.37 GB
Huihui-SmolLM3-3B-abliterated.Q3_K_L.gguf 1.57 GB 6ef9713c download
Huihui-SmolLM3-3B-abliterated.Q3_K_M.gguf 1.46 GB bf524722 download
Huihui-SmolLM3-3B-abliterated.Q3_K_S.gguf 1.33 GB 713b9859 download
Q2_K 1 file 1.17 GB
Huihui-SmolLM3-3B-abliterated.Q2_K.gguf 1.17 GB 68798627 download
Auxiliary files 2 files 6.10 KB
README.md 3.71 KB 4cab3d77 download
.gitattributes 2.39 KB 946da30b download

README current version from Hugging Face


base_model: huihui-ai/Huihui-SmolLM3-3B-abliterated
language:

  • en
  • fr
  • es
  • it
  • pt
  • zh
  • ar
  • ru
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored

About

static quants of https://huggingface.co/huihui-ai/Huihui-SmolLM3-3B-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/Huihui-SmolLM3-3B-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 1.4
GGUF Q3_K_S 1.5
GGUF Q3_K_M 1.7 lower quality
GGUF Q3_K_L 1.8
GGUF IQ4_XS 1.8
GGUF Q4_K_S 1.9 fast, recommended
GGUF Q4_K_M 2.0 fast, recommended
GGUF Q5_K_S 2.3
GGUF Q5_K_M 2.3
GGUF Q6_K 2.6 very good quality
GGUF Q8_0 3.4 fast, best quality
GGUF f16 6.3 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 3 versions

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

  1. 2025-07-15auto-patch README.mda22d8c93.7 KB
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  2. 2025-07-15auto-patch README.mdba66a483.8 KB
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  3. 2025-07-15uploaded from back01889ac229 B
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