Timber
Ollama for classical ML models.
Timber compiles trained tree-based models (XGBoost, LightGBM, scikit-learn, CatBoost, ONNX) into optimized native C and serves them over a local HTTP API.
No Python runtime in the inference hot path
Native latency (microseconds)
One command to load, one command to serve
📚 Docs: https://kossisoroyce.github.io/timber/
Who is this for?
Timber is built for teams that need fast, predictable, portable inference:
Fraud/risk teams running classical models in low-latency transaction paths
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