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Okardu/Huihui-Kolibri-1-abliterated-GGUF

Okardu GGUF MoE
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created 2026-10-08

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Metadata

License
apache-2.0
Languages
de en
Quantizations
Q4_K
Tags
vllm gguf abliterated uncensored huihui reasoning moe text-generation de en base_model:Aleph-Alpha/Kolibri-1 base_model:quantized:Aleph-Alpha/Kolibri-1

Related

Total size
44.6 GB
Files
4
Quantizations
2
Registered
2026-10-08 02:58
Last updated on HF
2026-10-08 02:50

Files by quantization

Q4_K 1 file 44.6 GB
Huihui-Kolibri-1-abliterated-Q4_K_M.gguf 44.6 GB c4d5d43a download
Auxiliary files 3 files 33.7 KB
kolibri1-llama.cpp.patch 29.1 KB d07c2702 download
README.md 2.90 KB e5c8d90d download
.gitattributes 1.74 KB 71a17ee9 download

README current version from Hugging Face


license: "apache-2.0"
pipeline_tag: text-generation
library_name: vllm
base_model: Aleph-Alpha/Kolibri-1
language:

  • de
  • en
    tags:
  • abliterated
  • uncensored
  • huihui
  • reasoning
  • moe

huihui-ai/Huihui-Kolibri-1-abliterated-GGUF

This is an uncensored version of Aleph-Alpha/Kolibri-1 created with abliteration.

This ablation was performed entirely using llama.cpp's GGUF model, without relying on Transformers,

For the specific ablation method, please refer to cvector-generator.

Note

GGUFs come from Hob-forge/Kolibri-1-GGUF.

The ablation did not modify all expert modules.

llama.cpp

Requires a llama.cpp patch

Stock llama.cpp does not support the kolibri1 architecture yet. Apply kolibri1-llama.cpp.patch (included in this repo) to llama.cpp at upstream commit 836d571, then build:

git clone https://github.com/ggml-org/llama.cpp && cd llama.cpp
git checkout 836d571
git am /path/to/kolibri1-llama.cpp.patch
cmake -B build -DCMAKE_BUILD_TYPE=Release   # add -DGGML_CUDA=ON etc. for your GPU
cmake --build build -j --target llama-server llama-cli

Running

llama-cli -m huihui-ai/Huihui-Kolibri-1-abliterated-GGUF/Huihui-Kolibri-1-abliterated-Q4_K_M.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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