VLN-CE provides an instruction-guided navigation task where agents follow natural language instructions to navigate through photorealistic continuous environments. The repository implements deep learning agents that process both visual observations and language instructions to produce navigation actions. It supports the Room-to-Room (R2R) and Room-Across-Room (RxR) datasets and builds upon Habitat-Sim and Habitat-Lab for realistic simulation and training infrastructure.