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andyjack/Huihui-Qwen3.6-27B-abliterated-GGUF

andyjack Qwen 27B GGUF multimodal 262K ctx
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Response includes
  • classification m8
  • files 6
  • benchmarks 11 entries
  • hub_downloads_all_time 34,456
  • author_summary 7 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
MEDIUM
Inherited from base model
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
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
34K
179 last 30d - cooling
Likes
1
Model age
5mo ago
created 2026-04-24
Downloads over time
Now34.5K→from3.9K↑786%
2.4K14.1K25.8K37.6K3.9K on Apr 2234.5K on Oct 11AprMayJunJulAugSepOct
Apr 22 → Oct 11 · 64 snapshots · spans 172 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Entertainment 1.2 UGI
Hazardous 4.7 UGI
Natural Intelligence 33.16 UGI
Political lean -20.0% UGI
Sensitive-Info 26.98 UGI
SocPol 2.9 UGI
UGI 27.15 UGI
Willingness (10) 2.8 UGI
W10-Adherence 1.5 UGI
W10-Direct 4 UGI
Writing 42.47 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.

Metadata

License
apache-2.0
Quantizations
Q4_K Q6_K Q8_0
Tags
transformers gguf abliterated uncensored image-text-to-text conversational base_model:Qwen/Qwen3.6-27B base_model:quantized:Qwen/Qwen3.6-27B license:apache-2.0 endpoints_compatible region:us

Related

Total size
62.6 GB
Files
6
Quantizations
5
Registered
2026-08-22 13:56
Last updated on HF
2026-07-06 18:38

Files by quantization

Q8_0 1 file 26.6 GB
Qwen3.6-27b-abliterated-Q8_0.gguf 26.6 GB 4ae8a9e3 download
Q6_K 1 file 20.6 GB
Qwen3.6-27b-abliterated-Q6_K.gguf 20.6 GB 12e83150 download
Q4_K 1 file 15.4 GB
Qwen3.6-27b-abliterated-Q4_K_M.gguf 15.4 GB 795a77ae download
F16 1 file 888 MB
mmproj-f16.gguf 888 MB 6bbcd5a5 download
Auxiliary files 2 files 10.4 KB
chat_template.jinja 7.58 KB a8755d82 download
README.md 2.80 KB 8b3dbf2b download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE
pipeline_tag: image-text-to-text
base_model:

  • Qwen/Qwen3.6-27B
    tags:
  • abliterated
  • uncensored

huihui-ai/Huihui-Qwen3.6-27B-abliterated

This is an uncensored version of Qwen/Qwen3.6-27B created with abliteration (see remove-refusals-with-transformers to know more about it).
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
I made GGUF's in Q8 and Q6 for almost perfect full quality and Q4_K_M to fit on a single RTX 3090 or 4090.
You can also export GGML_CUDA_ENABLE_UNIFIED_MEMORY=1 to enable unified memory on linux with Nvidia.
All model quants tested with mmproj-f16.gguf for multi-modal image use.

llama.cpp

llama.cpp/build/bin/llama-server \
  -m Qwen3.6-27b-abliterated-Q8_0.gguf \
  --mmproj mmproj-f16.gguf \
  --host 0.0.0.0 \
  --port 11434 \
  --api-key XXX \
  --flash-attn on \
  --cache-type-k q8_0 \
  --cache-type-v q8_0\
  --n-gpu-layers 99 \
  --split-mode layer \
  --no-mmap \
  --temp 0.7 \
  --top-p 0.95 \
  --top-k 20 \
  --repeat-penalty 1.0 \
  --jinja \
  -c 262144 \
  -b 2048 \
  -ub 2048 \
  --parallel 1

Usage Warnings

  • Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.

  • Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.

  • Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.

  • Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.

  • Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.

  • No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai nor I bear any responsibility for any consequences arising from its use.

Donation

Your donation helps us continue our further development and improvement, a cup of coffee can do it.
  • bitcoin:
bc1q6nvh39fcmy0de0ezepnn2z0rn4dme9yjal77ah

README history 16 versions

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

  1. 2026-07-06Update README.md075d8962.8 KB
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  2. 2026-06-21Update README.md347a12f2.8 KB
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  3. 2026-05-12Update README.mdd5ab27b2.8 KB
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  5. 2026-04-26Update README.md8b2f76e2.8 KB
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  6. 2026-04-24Update README.md07298152.9 KB
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  11. 2026-04-24Update README.mdfa353b12.9 KB
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  14. 2026-04-24Update README.mde15213d2.9 KB
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  15. 2026-04-24Upload folder using huggingface_hub8e42f402.6 KB
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  16. 2026-04-24initial commit90bdd7728 B
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