This repository provides a PyTorch implementation of Q-Transformer, a method for scalable offline reinforcement learning. It reproduces the autoregressive Q-learning formulation for handling continuous action spaces in robotics applications. The implementation includes a vision transformer backbone for processing high-dimensional observations like images, along with tools for environment interaction, replay memory management, and training agents using Q-learning on discrete action bins.