Graphormer is a general-purpose deep learning backbone designed for molecular modeling tasks. It leverages graph transformer architectures to accelerate AI-driven research in molecule science, including drug discovery and material discovery. The package supports pre-trained models, interfaces with popular graph libraries (PyG, DGL, OGB), and was the winning solution in the Open Catalyst Challenge.