Learn2learn accelerates the meta-learning research cycle by providing low-level utilities and unified interfaces for creating new algorithms and domains. It includes high-quality implementations of existing meta-learning algorithms, standardized benchmarks for few-shot learning, and environment utilities for meta-reinforcement learning. The library maintains compatibility with standard PyTorch ecosystem tools.