Search + Filter
timber
Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One...
Updated means this listing was last refreshed on Mar 24, 2026.
About timber
Pricing:Freemium
Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference. kossisoroyce/timber is an open source project on GitHub with 650 stars. Built primarily in Python. Topics: c99, catboost, compiler, decision-trees, gradient-boosting, inference, lightgbm, machine-learning, mlops, model-serving.
Pros
- •Accessible pricing model for early testing.
Cons
- •Pricing details are limited and may require visiting the official website.
- •Limited public review volume, so performance may vary by workflow.
- •No screenshots provided for quick visual evaluation.