Instructions to use mudler/KAT-Coder-V2.5-Dev-APEX-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 mudler/KAT-Coder-V2.5-Dev-APEX-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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF # Run inference directly in the terminal: ./llama-cli -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
Use Docker
docker model run hf.co/mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
- LM Studio
- Jan
- Ollama
How to use mudler/KAT-Coder-V2.5-Dev-APEX-GGUF with Ollama:
ollama run hf.co/mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
- Unsloth Studio
How to use mudler/KAT-Coder-V2.5-Dev-APEX-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 mudler/KAT-Coder-V2.5-Dev-APEX-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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mudler/KAT-Coder-V2.5-Dev-APEX-GGUF to start chatting
- Pi
How to use mudler/KAT-Coder-V2.5-Dev-APEX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
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": "mudler/KAT-Coder-V2.5-Dev-APEX-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mudler/KAT-Coder-V2.5-Dev-APEX-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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
Run Hermes
hermes
- OpenClaw new
How to use mudler/KAT-Coder-V2.5-Dev-APEX-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
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 "mudler/KAT-Coder-V2.5-Dev-APEX-GGUF" \ --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 mudler/KAT-Coder-V2.5-Dev-APEX-GGUF with Docker Model Runner:
docker model run hf.co/mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
- Lemonade
How to use mudler/KAT-Coder-V2.5-Dev-APEX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mudler/KAT-Coder-V2.5-Dev-APEX-GGUF
Run and chat with the model
lemonade run user.KAT-Coder-V2.5-Dev-APEX-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Test results
Hello,
so i have downloaded all the apex variants and used them via pydantic-deep asking the models to code in C++ without telling them which version, two files .cpp/.h
llama-server -m {model.gguf} --host localhost --port 8080 -t 8 -ngl 999 -b 512 -ub 256 -fa on -ncmoe 32 --jinja --temp 0.6 --top_k 20 --top_p 0.9 --min-p 0.0 --presence-penalty 0 --repeat-penalty 1.0 --parallel 1 --cont-batching --metrics --warmup --chat-template-file chat.jinja*
Config: RX 6700 XT 12GB Vram (Vulkan only) / R7 5700X / 32 GB / Archlinux
*--chat-template-file chat.jinja > They don't have the chat template injected
Score:
Rank | Model | C++ version | Score
π₯ 1 | APEX-I-Quality | C++17 | 8.0
π₯ 2 | APEX-I-Compact | C++17 | 7.5
π₯ 3 | APEX-Balanced | C++17 | 7.5
4 | APEX-I-Mini | C++11 | 6.5
5 | APEX-I-Balanced | C++14 | 6.5
6 | APEX-Quality | C++14 | 6.5
7 | APEX-Compact | C++11 | 5.5
I have noticed Quality and i Quality and balanced (i guess) > tend to review their codes and edit before they say it's done.