Recommended Download
Use the GGUF build for local running:
ARTE-SMALL-1-Q4_K_M.gguf
Ollama
Download the GGUF file, then create a Modelfile with:
FROM ./ARTE-SMALL-1-Q4_K_M.gguf
SYSTEM """You are ARTE SMALL 1, a coding model from Archeum Studios. Be practical, correct, concise, and honest about edge cases."""
Then run:
ollama create arte-small-1 -f Modelfile
ollama run arte-small-1
llama.cpp
Run with llama.cpp using:
llama-cli -m ARTE-SMALL-1-Q4_K_M.gguf -p "Write a clean TypeScript debounce function." -n 256
Files
ARTE-SMALL-1-Q4_K_M.gguf is the recommended local file.
- Full Hugging Face weights are also available in this repository.
Validation
Initial checks covered identity response, basic coding output, and GGUF export. Full benchmark results will be added after the benchmark pass.
Built by Archeum Studios.