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nuofang/Huihui-Qwen3.5-9B-abliterated-GGUF

nuofang Qwen 9B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 10
  • benchmarks 11 entries
  • hub_downloads_all_time 9,021
  • author_summary 22 models
  • readme_text full
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What "m8" means · taxonomy
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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
MEDIUM
Inherited from base model
M1 Direct removal →
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
How we label → About M8 →
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
9K
3K last 30d - stable
Likes
2
Model age
6mo ago
created 2026-03-17
Downloads over time
Now10.8K→from1.5K↑601%
1.1K4.6K8.1K11.7K1.5K on Mar 1810.8K on Oct 11MarAprMayJunJulAugSepOct
Mar 18 → Oct 11 · 69 snapshots · spans 207 days

Benchmarks

Benchmark Score Source
Entertainment 0.9 UGI
Hazardous 1.8 UGI
Natural Intelligence 14.88 UGI
Political lean -6.0% UGI
Sensitive-Info 11.44 UGI
SocPol 0.9 UGI
UGI 37.63 UGI
Willingness (10) 9 UGI
W10-Adherence 9 UGI
W10-Direct 9 UGI
Writing 29.12 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.

huihui-ai/Huihui-Qwen3.5-9B-abliterated↓ 6,645 this lineage
nuofang/Huihui-Qwen3.5-9B-abliterated-GGUF↓ 2,675

Metadata

Quantizations
Q4_K Q5_K
Tags
gguf llama.cpp quantized imatrix base_model:huihui-ai/Huihui-Qwen3.5-9B-abliterated base_model:quantized:huihui-ai/Huihui-Qwen3.5-9B-abliterated endpoints_compatible region:us conversational

Related

Other by nuofang
Qwen3.8-9B-Distill-SLERP-F451-Pro-Writer-Uncensored-GGUF 15K Qwen3.8-9B-Distill-uncensored-heretic-GGUF 4K Qwen3.8-9B-abliterated-25-GGUF 2K Qwen3.5-9B-The-Bradbury-F451-Pro-Writer-Uncensored-Heretic-GGUF 993 Qwen3.5-9B-Uncensored-HauhauCS-Aggressive-GGUF 793
Same base model
mradermacher/Huihui-Qwen3.5-9B-abliterated-GGUF 93K mradermacher/Huihui-Qwen3.5-9B-abliterated-i1-GGUF 15K Abiray/Huihui-Qwen3.5-9B-abliterated-GGUF 6K td-builder/Qwen3.5-9B-abliterated-GGUF 2K darkmaniac7/Qwen3.5-9B-uncensored-MNN 1K
Total size
32.0 GB
Files
10
Quantizations
4
Registered
2026-08-22 13:56
Last updated on HF
2026-08-01 22:05
Source huggingface.co/nuofang/Huihui-Qwen3.5-9B-abliterated-GGUF ↗ Base model huihui-ai/Huihui-Qwen3.5-9B-abliterated →

Files by quantization

Q5_K 2 files 11.9 GB
Huihui-Qwen3.5-9B-abliterated-Q5_K_M-no-mtp.gguf 6.02 GB 89ebd0ba download
Huihui-Qwen3.5-9B-abliterated-Q5_K_S-no-mtp.gguf 5.87 GB cff1c1e9 download
Q4_K 2 files 10.2 GB
Huihui-Qwen3.5-9B-abliterated-Q4_K_M-no-mtp.gguf 5.24 GB 0d797db9 download
Huihui-Qwen3.5-9B-abliterated-Q4_K_S-no-mtp.gguf 4.98 GB 9f39c508 download
F16 1 file 879 MB
mmproj-Huihui-Qwen3.5-9B-abliterated-f16.gguf 879 MB b77ecf23 download
Auxiliary files 5 files 9.89 GB
Huihui-Qwen3.5-9B-abliterated-IQ4_NL-no-mtp.gguf 5.05 GB f216f819 download
Huihui-Qwen3.5-9B-abliterated-IQ4_XS-no-mtp.gguf 4.84 GB 6df44fcc download
imatrix.gguf 4.91 MB 3ce9be4a download
.gitattributes 2.50 KB 84b830bf download
README.md 1.39 KB f66672d1 download

README current version from Hugging Face

base_model: huihui-ai/Huihui-Qwen3.5-9B-abliterated
tags:

  • llama.cpp
  • quantized
  • imatrix

Auto-Quantized GGUF Model

This repository contains automated GGUF quantization files for huihui-ai/Huihui-Qwen3.5-9B-abliterated.

The calibration data for the imatrix is targeted at Chinese novels and role-playing (RP), while preserving logic and common sense.
imatrix 的校准数据以中文的小说、角色扮演为目标，同时保留逻辑和常识。

If the perplexity drops after quantization compared to the original precision, it might not actually be an improvement. Instead, it could be caused by differences in how llama.cpp quantization and perplexity tools handle special tokens. I will update the README generation code in the future.
如果困惑度在量化之后与原精度相比变低，可能并不是真的提升，而是llamacpp量化工具和困惑度计算工具处理特殊token行为不同导致的，我将在未来修改生成readme的代码。

Perplexity Evaluation

(Tested against the provided calibration dataset)

  • Base (F16/BF16): PPL = 16.9588 +/- 0.14520
  • IQ4_XS: PPL = 14.1837 +/- 0.11750
  • IQ4_NL: PPL = 14.1609 +/- 0.11721
  • Q4_K_S: PPL = 14.1113 +/- 0.11654
  • Q4_K_M: PPL = 14.0858 +/- 0.11636
  • Q5_K_S: PPL = 13.9766 +/- 0.11525
  • Q5_K_M: PPL = 13.9731 +/- 0.11528

README history 14 versions

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

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