treelite
A universal model exchange and serialization format for decision tree forests, enabling cross-platform deployment.
What is treelite?
Treelite is a universal model exchange and serialization format for decision tree forests. It enables machine learning practitioners to store, share, and deploy tree-based models consistently across different platforms and applications, solving the problem of model deployment fragmentation.
Machine learning engineers and data scientists working with decision tree models (e.g., random forests, gradient boosting) who need to deploy models in production C++ applications.
Developers choose Treelite because it provides a standardized, lightweight solution for model interoperability, eliminating the need for custom deployment code and ensuring consistent model behavior across different systems.
Overview
Universal model exchange and serialization format for decision tree forests
Use Cases
Best For
- Deploying tree-based models in C++ production environments
- Exchanging decision tree models between different machine learning frameworks
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