  Green Tsetlin (GT) is a Tsetlin Machine (TM) framework developed to solve
real-world problems using TMs. Several frameworks already exist that provide
access to TM implementations. However, these either lack features or have a
research-first focus. GT is an easy-to-use framework that aims to lower the
complexity and provide a production-ready TM implementation that is great for
experienced practitioners and beginners. To this end, GT establishes a clear
separation between training and inference. A C++ backend with a Python
interface provides competitive training and inference performance, with the
option of running in pure Python. It also integrates support for critical
components such as exporting trained models, hyper-parameter search, and
cross-validation out-of-the-box.
