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karlsencoin/Karlsen-Chat-27B-abliterated-GGUF

karlsencoin Qwen 27B GGUF multimodal
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? →
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Metadata

License
apache-2.0
Quantizations
IQ4
Tags
transformers gguf abliterated uncensored huihui qwen3 unsloth image-text-to-text base_model:Qwen/Qwen3.8-27B base_model:quantized:Qwen/Qwen3.8-27B license:apache-2.0 endpoints_compatible

Related

Total size
13.4 GB
Files
6
Quantizations
3
Registered
2026-09-11 20:55
Last updated on HF
2026-09-11 20:32

Files by quantization

IQ4 1 file 13.4 GB
Huihui-Qwen3.8-27B-abliterated-UD-IQ4_XS.gguf 13.4 GB d83adbbb download
BF16 1 file 888 MB
mmproj-model-bf16.gguf 888 MB c9a09064 download
Auxiliary files 4 files 10.2 KB
README.md 5.38 KB 23c26bec download
.gitattributes 4.56 KB e24cd6d3 download
Qwen3.8-27B-tensor_types-Q6_K_L.txt 123 B 34440335 download
Qwen3.8-27B-tensor_types-Q8_0_L.txt 123 B b06f0153 download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
pipeline_tag: image-text-to-text
base_model:

  • Qwen/Qwen3.8-27B
    tags:
  • abliterated
  • uncensored
  • huihui
  • qwen3
  • unsloth

huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF

This is an uncensored version of Qwen/Qwen3.8-27B 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.

Latest update 5

The newly added Huihui-Qwen3.8-27B-abliterated-GSQ-RCO series come from ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF.
Only layers 23 to 51 have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning.
The size after conversion may differ from the original GGUF.

Latest update 4

The newly added Huihui-Qwen3.8-27B-abliterated-UD-DW series come from unsloth/Qwen3.8-27B-GGUF.
Only layers 23 to 51 have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning.
The size after conversion may differ from the original GGUF.

Latest update

The newly added Huihui-Qwen3.8-27B-abliterated-UD series come from unsloth/Qwen3.8-27B-GGUF.
Only layers 18 to 51 have been ablated(Previously, The first 15 layers were retained without ablation), while the other layers remain unablated.
The size after conversion may differ from the original GGUF.

Huihui-Qwen3.8-27B-abliterated-bf16.gguf has also been updated.

This helps retain more of the original model’s performance. MTP and visual has not been modified.

Note

The first 15 layers were retained without ablation. MTP and visual has not been modified.

We have already converted the weights (token_embd,output,ffn_down,ssm_out,attn_output) that need to be ablated in the versions below Q8_0 from Q2_K, Q3_K, Q4_K, Q5_K, and Q6_K to Q8_0 to improve response quality, and changed the filename to K_L.

In the Q8_0 quantized version, we changed the Q8_0 weights (token_embd,output,ffn_down,ssm_out,attn_output) targeted for ablation to BF16 and renamed the file to Q8_0_L.

This is not a standard quantization, so you might find that Q2_K_L is larger than Q3_K and Q4_K.

Specific Quantification Method

Some people may misunderstand. The specific quantification method is as follows.

Q2_K_L - Q6_K_L

Qwen3.8-27B-tensor_types-Q6_K_L.txt

llama-quantize \
  --allow-requantize \
  --tensor-type-file huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Qwen3.8-27B-tensor_types-Q6_K_L.txt \
  huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Huihui-Qwen3.8-27B-abliterated-bf16.gguf \
  huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Huihui-Qwen3.8-27B-abliterated-Q6_K_L.gguf Q6_K

Q8_0_L

Qwen3.8-27B-tensor_types-Q8_0_L.txt

llama-quantize \ 
  --allow-requantize \
  --tensor-type-file huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Qwen3.8-27B-tensor_types-Q8_0_L.txt \
  huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Huihui-Qwen3.8-27B-abliterated-bf16.gguf \ 
  huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Huihui-Qwen3.8-27B-abliterated-Q8_0_L.gguf Q8_0

ollama

Please use the latest version of ollama

You can use huihui_ai/Qwen3.8-abliterated directly,

ollama run huihui_ai/Qwen3.8-abliterated

llama.cpp

Use the latest llama.cpp,

llama-cli -m huihui-ai/Huihui-Qwen3.8-27B-abliterated-GGUF/Huihui-Qwen3.8-27B-abliterated-Q4_K.gguf -c 262144

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 bears no responsibility for any consequences arising from its use.

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