Text Generation
GGUF
English
ollama
lm-studio
llama-cpp
computercraft
cc-tweaked
minecraft
lua
code
conversational
Instructions to use minecartchris/cc-coder-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 minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf minecartchris/cc-coder-GGUF:Q4_K_M
Use Docker
docker model run hf.co/minecartchris/cc-coder-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use minecartchris/cc-coder-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "minecartchris/cc-coder-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": "minecartchris/cc-coder-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/minecartchris/cc-coder-GGUF:Q4_K_M
- Ollama
How to use minecartchris/cc-coder-GGUF with Ollama:
ollama run hf.co/minecartchris/cc-coder-GGUF:Q4_K_M
- Unsloth Studio
How to use minecartchris/cc-coder-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 minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for minecartchris/cc-coder-GGUF to start chatting
- Pi
How to use minecartchris/cc-coder-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf minecartchris/cc-coder-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": "minecartchris/cc-coder-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use minecartchris/cc-coder-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf minecartchris/cc-coder-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 "minecartchris/cc-coder-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"
- Docker Model Runner
How to use minecartchris/cc-coder-GGUF with Docker Model Runner:
docker model run hf.co/minecartchris/cc-coder-GGUF:Q4_K_M
- Lemonade
How to use minecartchris/cc-coder-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull minecartchris/cc-coder-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.cc-coder-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use minecartchris/cc-coder-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 minecartchris/cc-coder-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 minecartchris/cc-coder-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
| base_model: minecartchris/cc-coder | |
| license: other | |
| license_name: qwen-research | |
| license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct/blob/main/LICENSE | |
| language: | |
| - en | |
| tags: | |
| - gguf | |
| - ollama | |
| - lm-studio | |
| - llama-cpp | |
| - computercraft | |
| - cc-tweaked | |
| - minecraft | |
| - lua | |
| - code | |
| pipeline_tag: text-generation | |
| # cc-coder GGUF — CC: Tweaked Lua coding model for Ollama / LM Studio | |
| Quantized q4_k_m build (~1.9GB, runs comfortably on any modern machine — | |
| CPU-only works too) of | |
| [minecartchris/cc-coder](https://huggingface.co/minecartchris/cc-coder), | |
| a Qwen2.5-Coder-3B fine-tune for writing **CC: Tweaked (ComputerCraft)** | |
| Lua: turtles, peripherals, rednet, monitors, and community libraries. | |
| Evaluated by actually *running* its generated programs in a CraftOS-PC | |
| emulator: **74%** of everyday CC task generations run cleanly, **97%** | |
| parse. Full methodology on the adapter page. | |
| ## Run with Ollama | |
| Straight from this repo, no download step: | |
| ``` | |
| ollama run hf.co/minecartchris/cc-coder-GGUF | |
| ``` | |
| Then ask away: | |
| ``` | |
| >>> Write a turtle program that strip-mines a 2x1 tunnel for 32 blocks, | |
| placing torches every 8 blocks, and returns home when done. | |
| ``` | |
| ## Run with LM Studio | |
| Search for **cc-coder** in LM Studio's model search (or paste | |
| `minecartchris/cc-coder-GGUF`), download the q4_k_m file, and chat. | |
| Suggested settings: temperature 0.4, context 4096. | |
| ## Notes | |
| - The model prefers built-in CC APIs (`turtle`, `rednet`, `peripheral`, | |
| `fs`, `os.pullEvent`, `textutils`) and knows the correct `require` | |
| idioms for popular libraries (Basalt, Pine3D, PixelUI, ccryptolib, ...) | |
| - 3B model: always eyeball the logic before trusting a turtle with your | |
| diamonds | |
| - Qwen Research license inherited from the base model (non-commercial | |
| restrictions apply) | |