Instructions to use ccore/Qwen3.5-4B-3D-Coder 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 ccore/Qwen3.5-4B-3D-Coder 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 ccore/Qwen3.5-4B-3D-Coder:Q4_K_M # Run inference directly in the terminal: llama cli -hf ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ccore/Qwen3.5-4B-3D-Coder:Q4_K_M # Run inference directly in the terminal: llama cli -hf ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf ccore/Qwen3.5-4B-3D-Coder:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
Use Docker
docker model run hf.co/ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use ccore/Qwen3.5-4B-3D-Coder with Ollama:
ollama run hf.co/ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
- Unsloth Desktop
- Pi
How to use ccore/Qwen3.5-4B-3D-Coder with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ccore/Qwen3.5-4B-3D-Coder: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": "ccore/Qwen3.5-4B-3D-Coder:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use ccore/Qwen3.5-4B-3D-Coder with Docker Model Runner:
docker model run hf.co/ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
- Lemonade
How to use ccore/Qwen3.5-4B-3D-Coder with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.5-4B-3D-Coder-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use ccore/Qwen3.5-4B-3D-Coder with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ccore/Qwen3.5-4B-3D-Coder: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 ccore/Qwen3.5-4B-3D-Coder:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ccore/Qwen3.5-4B-3D-Coder with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ccore/Qwen3.5-4B-3D-Coder: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 "ccore/Qwen3.5-4B-3D-Coder: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"
Requests help installing as ollama model with tools usage
I tried different approaches - but ends with thinking but still tools usage disabled model. While it is very useful for godot (already) and blender. But cannot use MCP or simple function calling and returns result as answer only
I tried different approaches - but ends with thinking but still tools usage disabled model. While it is very useful for godot (already) and blender. But cannot use MCP or simple function calling and returns result as answer only
Check this out https://ollama.com/maternion/qwen3.5-3d-coder
Make sure to set a higher context length!
And so you don't struggle with newer models later, Ollama has moved to PARSER/RENDERER or Embedded Jinja Templates instead of their Go Templates mostly.
So you can either rely on the GGUF's jinja template and make a Modelfile like this -
FROM model.gguf
FROM mmproj.gguf
TEMPLATE {{ .Prompt }}
PARAMETERS ...
or you can use the renderer/parser for that model which should in theory work better.
FROM qwen3.5.gguf
FROM mmproj.gguf
TEMPLATE {{ .Prompt }}
RENDERER qwen3.5
PARSER qwen3.5
PARAMETERS ...
the renderer parser names are mostly the arch name in the model's config. But it can vary and I am not sure about a reliable way to verify this. Some just check the renderer parser directories in the source code.
If you have a working model then locally you can run ollama show model and in the newer versions it shows if the model uses a GGUF template or renderer/parser and their names too. It's however not shown on ollama.com/library.