Instructions to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Use Docker
docker model run hf.co/huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "huihui-ai/Huihui-Kolibri-1-abliterated-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "huihui-ai/Huihui-Kolibri-1-abliterated-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
- Ollama
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with Ollama:
ollama run hf.co/huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with Docker Model Runner:
docker model run hf.co/huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
- Lemonade
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Huihui-Kolibri-1-abliterated-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use huihui-ai/Huihui-Kolibri-1-abliterated-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "huihui-ai/Huihui-Kolibri-1-abliterated-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
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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