The first full-fledged version of multifidelity machine learning software has been released by Vivin Vinod under the MIT license at PyPi for use in quantum chemistry applications. With a detailed documentation of the library and examples at https://vivinvinod.github.io/mfml-4-qc , the lightweight NUMBA accelerated package provides users with easy to deploy resources of multifidelity machine learning. Flexibility of machine learning architecture and cutting edge integration of numerical compute engines such as ORCA make mfml-4-qc a highly modular package. Active learning using the efficient Low Fidelity as Bias technique is also provided.