The Radial Basis Function (RBF) method to compute Lyapunov functions for nonlinear systems uses generalized interpolation in Reproducing Kernel Hilbert spaces. We present two different implementation in C++. One that is computationally efficient and one that is memory efficient. The former uses standard functions of a numerical library and the latter directly calls LAPACK routines for packed matrices to perform in-place Cholesky factorization of the interpolation matrix. The memory efficient implementation only needs one-fourth of the memory needed when using a standard numerical library and thus makes it possible to use double the amount of collocation points. Both implementations are easily adapted to different generalized interpolation problems.