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mradermacher/Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030-GGUF

mradermacher Qwen 30B GGUF MoE second-order 262K ctx
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Response includes
  • classification m8
  • files 13
  • hub_downloads_all_time 4,639
  • 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-Qwen3-30B-A3B-abliterated-Fusion-7030' (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
5K
306 last 30d - cooling
Likes
1
Model age
13mo ago
created 2025-09-12
Downloads over time
Now4.7K→from2.2K↑112%
2.1K3K4K4.9K2.2K on Sep 10, 20254.7K on Oct 11Sep '25Nov '25JanMarMayJulSep
Sep 10, 2025 → Oct 11 · 96 snapshots · spans 396 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
mit
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf chat Fusion en license:mit endpoints_compatible region:us conversational

Related

Total size
194 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2025-09-12 14:47

Files by quantization

Q8_0 1 file 30.3 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q8_0.gguf 30.3 GB e985f3c8 download
Q6_K 1 file 23.4 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q6_K.gguf 23.4 GB a5d412d6 download
Q5_K 2 files 39.9 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q5_K_M.gguf 20.2 GB 1d5a8444 download
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q5_K_S.gguf 19.6 GB 19a8adff download
Q4_K 2 files 33.5 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q4_K_M.gguf 17.3 GB a0e5effa download
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q4_K_S.gguf 16.3 GB 1215fc5d download
IQ4 1 file 15.4 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.IQ4_XS.gguf 15.4 GB e23387bf download
Q3_K 3 files 40.9 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q3_K_L.gguf 14.8 GB 20238434 download
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q3_K_M.gguf 13.7 GB d5cd0e59 download
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q3_K_S.gguf 12.4 GB 2d5e7be8 download
Q2_K 1 file 10.5 GB
Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030.Q2_K.gguf 10.5 GB 3db3f17e download
Auxiliary files 2 files 6.51 KB
README.md 4.04 KB 71f4b06e download
.gitattributes 2.48 KB 4af7aa01 download

README current version from Hugging Face


base_model: huihui-ai/Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030
language:

  • en
    library_name: transformers
    license: mit
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • chat
  • Fusion

About

static quants of https://huggingface.co/huihui-ai/Huihui-Qwen3-30B-A3B-abliterated-Fusion-7030

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-Qwen3-30B-A3B-abliterated-Fusion-7030-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 11.4
GGUF Q3_K_S 13.4
GGUF Q3_K_M 14.8 lower quality
GGUF Q3_K_L 16.0
GGUF IQ4_XS 16.7
GGUF Q4_K_S 17.6 fast, recommended
GGUF Q4_K_M 18.7 fast, recommended
GGUF Q5_K_S 21.2
GGUF Q5_K_M 21.8
GGUF Q6_K 25.2 very good quality
GGUF Q8_0 32.6 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 3 versions

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

  1. 2025-09-12auto-patch README.mdcf9ef474 KB
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  2. 2025-09-12auto-patch README.mdb2561334 KB
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  3. 2025-09-12uploaded from nico1858a9d4396 B
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