Instructions to use kai-os/Carnice-9b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use kai-os/Carnice-9b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="kai-os/Carnice-9b-GGUF", filename="Carnice-9b-Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kai-os/Carnice-9b-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kai-os/Carnice-9b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf kai-os/Carnice-9b-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf kai-os/Carnice-9b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf kai-os/Carnice-9b-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 kai-os/Carnice-9b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf kai-os/Carnice-9b-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 kai-os/Carnice-9b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf kai-os/Carnice-9b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/kai-os/Carnice-9b-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use kai-os/Carnice-9b-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kai-os/Carnice-9b-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": "kai-os/Carnice-9b-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/kai-os/Carnice-9b-GGUF:Q4_K_M
- Ollama
How to use kai-os/Carnice-9b-GGUF with Ollama:
ollama run hf.co/kai-os/Carnice-9b-GGUF:Q4_K_M
- Unsloth Studio
How to use kai-os/Carnice-9b-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kai-os/Carnice-9b-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kai-os/Carnice-9b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kai-os/Carnice-9b-GGUF to start chatting
- Pi
How to use kai-os/Carnice-9b-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf kai-os/Carnice-9b-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "kai-os/Carnice-9b-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use kai-os/Carnice-9b-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf kai-os/Carnice-9b-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 kai-os/Carnice-9b-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use kai-os/Carnice-9b-GGUF with Docker Model Runner:
docker model run hf.co/kai-os/Carnice-9b-GGUF:Q4_K_M
- Lemonade
How to use kai-os/Carnice-9b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kai-os/Carnice-9b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Carnice-9b-GGUF-Q4_K_M
List all available models
lemonade list
The model refuses to do research
I asked this model to do research on stock tickers via the llm-wiki skill. This model to give recommendations based on current geopolitical conditions citing "i'm not a financial advisor, I will not cross that line." Not sure if its a byproduct of the finetuneing or the small model size but my gosh it is infuriating. Went back to regular qwen 122b and did all the research without refusal. Why is this?
during my tests, carnice-27b completely collapsed under my tests whereas even qwen3.5-35b-a3b-instruct IQ3_XXS completed 6/7 tasks fine. carnice-27b only passed one by chance