Caffe is a deep learning framework designed with emphasis on expression, speed, and modularity. It provides a BSD-licensed implementation of neural network layers, data layers, and solvers for training and deploying models. The framework supports GPU acceleration and has specialized distributions for Intel CPUs and OpenCL devices. BAIR provides reference models through its model zoo.