Instructions to use arcee-ai/Homunculus-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arcee-ai/Homunculus-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arcee-ai/Homunculus-GGUF", dtype="auto") - llama-cpp-python
How to use arcee-ai/Homunculus-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="arcee-ai/Homunculus-GGUF", filename="Homunculus-IQ2_M.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 arcee-ai/Homunculus-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf arcee-ai/Homunculus-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf arcee-ai/Homunculus-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf arcee-ai/Homunculus-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf arcee-ai/Homunculus-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 arcee-ai/Homunculus-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf arcee-ai/Homunculus-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 arcee-ai/Homunculus-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf arcee-ai/Homunculus-GGUF:Q4_K_M
Use Docker
docker model run hf.co/arcee-ai/Homunculus-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use arcee-ai/Homunculus-GGUF with Ollama:
ollama run hf.co/arcee-ai/Homunculus-GGUF:Q4_K_M
- Unsloth Studio new
How to use arcee-ai/Homunculus-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 arcee-ai/Homunculus-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 arcee-ai/Homunculus-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for arcee-ai/Homunculus-GGUF to start chatting
- Pi new
How to use arcee-ai/Homunculus-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf arcee-ai/Homunculus-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": "arcee-ai/Homunculus-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use arcee-ai/Homunculus-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf arcee-ai/Homunculus-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 arcee-ai/Homunculus-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use arcee-ai/Homunculus-GGUF with Docker Model Runner:
docker model run hf.co/arcee-ai/Homunculus-GGUF:Q4_K_M
- Lemonade
How to use arcee-ai/Homunculus-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull arcee-ai/Homunculus-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Homunculus-GGUF-Q4_K_M
List all available models
lemonade list
Extremely sensitive to parameters
I'm testing a Q5_K_S, so one would think it would behave well. However, the model is extremely sensitive to generation parameters and with the recommended ones, it actually devolves into a loop where it starts outputting less and less coherent thinking messages and finally just spouts nonsense words.
The only parameter combination I've actually succeeded with to get coherent output out of the models looks like this:
- temperature: 0.5
- top_k: 15 (!)
- repeat_penalty: 1.1
- min_p: 0
- top_p: 0.9