A robust tensor-based deep learning framework for solving partial differential equations using hp-Variational Physics-Informed Neural Networks (hp-VPINNs). The framework is based on the methodology presented in the FastVPINNs Paper. This library is a highly optimised version of the the initial implementation of hp-VPINNs by Kharazmi et al. at github link. Refer the hp-VPINNs Paper for more details. The FastVPINNs framework can achieve close to 100x speedup in training time of hp-VPINNs, when compared with the existing implementation of the hp-VPINNs and it can handle complex geometries. For More Details refer to https://github.com/cmgcds/fastvpinns.