This repository provides implementations of Recurrent Highway Networks, a neural network architecture that extends LSTM with highway layers to enable deeper recurrent state transitions. The project enables training RHN models for word-level language modeling tasks on datasets like Penn Treebank. Implementations are provided for Tensorflow, Torch7, Theano, and Brainstorm, allowing researchers to compare performance across frameworks and reproduce benchmark results.