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

mradermacher/Huihui-GLM-4.7-Flash-abliterated-GGUF

mradermacher Glm GGUF second-order 203K ctx
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Response includes
  • classification m8
  • files 13
  • benchmarks 11 entries
  • hub_downloads_all_time 94,917
  • 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-GLM-4.7-Flash-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
95K
7K last 30d - cooling
Likes
20
Model age
8mo ago
created 2026-01-22
Downloads over time
Now100K→from1.7K↑5,625%
036.6K73.2K109.8K1.7K on Jan 21100K on Oct 11JanMarMayJulSep
Jan 21 → Oct 11 · 78 snapshots · spans 263 days

Benchmarks

Benchmark Score Source
Entertainment 1.4 UGI
Hazardous 0.6 UGI
Natural Intelligence 18.32 UGI
Political lean -10.3% UGI
Sensitive-Info 12.1 UGI
SocPol 1.5 UGI
UGI 31.4 UGI
Willingness (10) 7 UGI
W10-Adherence 7 UGI
W10-Direct 7 UGI
Writing 25.08 UGI

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 · 26K downloads combined

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

Metadata

License
mit
Languages
en zh
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored en zh base_model:huihui-ai/Huihui-GLM-4.7-Flash-abliterated base_model:quantized:huihui-ai/Huihui-GLM-4.7-Flash-abliterated license:mit endpoints_compatible region:us conversational

Related

Total size
190 GB
Files
13
Quantizations
8
Registered
2026-08-22 13:56
Last updated on HF
2026-01-22 21:56

Files by quantization

Q8_0 1 file 29.7 GB
Huihui-GLM-4.7-Flash-abliterated.Q8_0.gguf 29.7 GB 46d025ee download
Q6_K 1 file 22.9 GB
Huihui-GLM-4.7-Flash-abliterated.Q6_K.gguf 22.9 GB 2ee3ba05 download
Q5_K 2 files 39.0 GB
Huihui-GLM-4.7-Flash-abliterated.Q5_K_M.gguf 19.8 GB 62719185 download
Huihui-GLM-4.7-Flash-abliterated.Q5_K_S.gguf 19.2 GB ddf7a097 download
Q4_K 2 files 32.8 GB
Huihui-GLM-4.7-Flash-abliterated.Q4_K_M.gguf 16.9 GB ca247d43 download
Huihui-GLM-4.7-Flash-abliterated.Q4_K_S.gguf 15.9 GB 9ef1554d download
IQ4 1 file 15.1 GB
Huihui-GLM-4.7-Flash-abliterated.IQ4_XS.gguf 15.1 GB f2a67a1b download
Q3_K 3 files 40.1 GB
Huihui-GLM-4.7-Flash-abliterated.Q3_K_L.gguf 14.5 GB 8584e926 download
Huihui-GLM-4.7-Flash-abliterated.Q3_K_M.gguf 13.4 GB 660c7be1 download
Huihui-GLM-4.7-Flash-abliterated.Q3_K_S.gguf 12.1 GB 37144367 download
Q2_K 1 file 10.3 GB
Huihui-GLM-4.7-Flash-abliterated.Q2_K.gguf 10.3 GB 6f52fe96 download
Auxiliary files 2 files 6.10 KB
README.md 3.75 KB 8d6e8470 download
.gitattributes 2.35 KB 99cb9d6d download

README current version from Hugging Face


base_model: huihui-ai/Huihui-GLM-4.7-Flash-abliterated
language:

  • en
  • zh
    library_name: transformers
    license: mit
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored

About

static quants of https://huggingface.co/huihui-ai/Huihui-GLM-4.7-Flash-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-GLM-4.7-Flash-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 11.1
GGUF Q3_K_S 13.1
GGUF Q3_K_M 14.5 lower quality
GGUF Q3_K_L 15.7
GGUF IQ4_XS 16.3
GGUF Q4_K_S 17.2 fast, recommended
GGUF Q4_K_M 18.2 fast, recommended
GGUF Q5_K_S 20.8
GGUF Q5_K_M 21.4
GGUF Q6_K 24.7 very good quality
GGUF Q8_0 31.9 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 6 versions

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

  1. 2026-01-22auto-patch README.md2d925ab3.7 KB
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  2. 2026-01-22auto-patch README.mdfc742f63.7 KB
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  3. 2026-01-22auto-patch README.md507c0eb3.5 KB
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  4. 2026-01-22auto-patch README.md6e108573 KB
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  5. 2026-01-22auto-patch README.mdd1b11312.4 KB
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  6. 2026-01-22uploaded from rich16815149385 B
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Discussions 1 thread

  1. 2026-01-24Thanks againopen1 💬#1
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