Instructions to use mach-kernel/ecu-pilot-q8_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use mach-kernel/ecu-pilot-q8_0 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mach-kernel/ecu-pilot-q8_0", filename="ecu-pilot-q8_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use mach-kernel/ecu-pilot-q8_0 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mach-kernel/ecu-pilot-q8_0:Q8_0 # Run inference directly in the terminal: llama-cli -hf mach-kernel/ecu-pilot-q8_0:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mach-kernel/ecu-pilot-q8_0:Q8_0 # Run inference directly in the terminal: llama-cli -hf mach-kernel/ecu-pilot-q8_0:Q8_0
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 mach-kernel/ecu-pilot-q8_0:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf mach-kernel/ecu-pilot-q8_0:Q8_0
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 mach-kernel/ecu-pilot-q8_0:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf mach-kernel/ecu-pilot-q8_0:Q8_0
Use Docker
docker model run hf.co/mach-kernel/ecu-pilot-q8_0:Q8_0
- LM Studio
- Jan
- Ollama
How to use mach-kernel/ecu-pilot-q8_0 with Ollama:
ollama run hf.co/mach-kernel/ecu-pilot-q8_0:Q8_0
- Unsloth Studio new
How to use mach-kernel/ecu-pilot-q8_0 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 mach-kernel/ecu-pilot-q8_0 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 mach-kernel/ecu-pilot-q8_0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mach-kernel/ecu-pilot-q8_0 to start chatting
- Pi new
How to use mach-kernel/ecu-pilot-q8_0 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mach-kernel/ecu-pilot-q8_0:Q8_0
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": "mach-kernel/ecu-pilot-q8_0:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mach-kernel/ecu-pilot-q8_0 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mach-kernel/ecu-pilot-q8_0:Q8_0
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 mach-kernel/ecu-pilot-q8_0:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use mach-kernel/ecu-pilot-q8_0 with Docker Model Runner:
docker model run hf.co/mach-kernel/ecu-pilot-q8_0:Q8_0
- Lemonade
How to use mach-kernel/ecu-pilot-q8_0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mach-kernel/ecu-pilot-q8_0:Q8_0
Run and chat with the model
lemonade run user.ecu-pilot-q8_0-Q8_0
List all available models
lemonade list
ecu-pilot (GGUF Q8_0)
Quantized GGUF of ecu-pilot-fp16 — a fine-tuned Qwen3.5-35B-A3B for structured tool calling against project metadata via MCP.
Quantization
| Source | mach-kernel/ecu-pilot-fp16 |
| Method | Q8_0 via llama.cpp |
| Size | ~35 GB |
| Architecture | Mixture of Experts (35B total, 3B active per token) |
Usage
Ollama
echo 'FROM ./ecu-pilot-q8_0.gguf
PARAMETER temperature 0.2
PARAMETER num_ctx 8192
PARAMETER stop <|im_end|>' > Modelfile
ollama create ecu-pilot -f Modelfile
ollama run ecu-pilot
llama.cpp
llama-cli -m ecu-pilot-q8_0.gguf -ngl 99 -cnv
All variants
| Format | Repository | Size |
|---|---|---|
| FP16 | mach-kernel/ecu-pilot-fp16 | ~67 GB |
| GGUF Q4_K_M | mach-kernel/ecu-pilot-q4km | ~20 GB |
| GGUF Q8_0 (this repo) | mach-kernel/ecu-pilot-q8_0 | ~35 GB |
| LoRA adapter | mach-kernel/ecu-pilot-fp16-lora | ~4 GB |
Why "ecu"
No reason. Just liked how it sounded. Definitely not a Caesar cipher of anything. Don't look into it.
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Hardware compatibility
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Base model
Qwen/Qwen3.5-35B-A3B-Base