This repository provides a PyTorch implementation of the MagViT2 tokenizer from the paper ‘Language Model Beats Diffusion - Tokenizer is Key to Visual Generation’. The tokenizer converts video frames into discrete tokens using a Lookup Free Quantizer and transformer-based architecture, enabling efficient video understanding and generation. It supports configurable image sizes, codebook sizes, and layer structures for training custom video tokenizers.