Instructions to use unsloth/North-Mini-Code-1.0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/North-Mini-Code-1.0-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/North-Mini-Code-1.0-GGUF", dtype="auto") - llama-cpp-python
How to use unsloth/North-Mini-Code-1.0-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unsloth/North-Mini-Code-1.0-GGUF", filename="BF16/North-Mini-Code-1.0-BF16-00001-of-00002.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use unsloth/North-Mini-Code-1.0-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 unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M # Run inference directly in the terminal: llama cli -hf unsloth/North-Mini-Code-1.0-GGUF:UD-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 unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf unsloth/North-Mini-Code-1.0-GGUF:UD-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 unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
Use Docker
docker model run hf.co/unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
- LM Studio
- Jan
- Ollama
How to use unsloth/North-Mini-Code-1.0-GGUF with Ollama:
ollama run hf.co/unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
- Unsloth Studio
How to use unsloth/North-Mini-Code-1.0-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 unsloth/North-Mini-Code-1.0-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 unsloth/North-Mini-Code-1.0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/North-Mini-Code-1.0-GGUF to start chatting
- Pi
How to use unsloth/North-Mini-Code-1.0-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/North-Mini-Code-1.0-GGUF:UD-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": "unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use unsloth/North-Mini-Code-1.0-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 unsloth/North-Mini-Code-1.0-GGUF:UD-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 unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use unsloth/North-Mini-Code-1.0-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf unsloth/North-Mini-Code-1.0-GGUF:UD-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 "unsloth/North-Mini-Code-1.0-GGUF:UD-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"
- Docker Model Runner
How to use unsloth/North-Mini-Code-1.0-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
- Lemonade
How to use unsloth/North-Mini-Code-1.0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/North-Mini-Code-1.0-GGUF:UD-Q4_K_M
Run and chat with the model
lemonade run user.North-Mini-Code-1.0-GGUF-UD-Q4_K_M
List all available models
lemonade list
Fails to load on LM Studio 0.4.16 (Build 2)
Fails to load on LM Studio 0.4.16 (Build 2)
Fails to load on LM Studio 0.4.16 (Build 2)
You need to manually install llama.cpp with PR #24260. LM Studio doesn't ship with this runtime right now. I suggest looking at the model card.
These are GGUF quants of North-Mini-Code-1.0. The model uses the cohere2moe architecture, which is not in a stock llama.cpp release yet. Until llama.cpp PR #24260 is merged, build llama.cpp from that PR branch to load these files. Once the PR lands in a release, these same GGUFs will run on stock llama.cpp with no re-download, because they already declare general.architecture = cohere2moe.
Even with PR #24260 being merged it didn't work for me in llama.cpp. So something seems still off or I am blind π
EDIT: Seems to work with the latest release after https://github.com/ggml-org/llama.cpp/pull/24260 got merged.
Yes, i still get PEG errors with tool calls, it loads for chat just fine but it cant handle tool calls in any harness (for me). Tried both PR #24260 and the latest llama.cpp. Putting this one to the side for now, hopefully it gets solved - looks like an interesting model.