Transfer Learning ToolKit for AI Optimization (TAO)

Transfer learning is a powerful technique that instantly transfers learned features from an existing neural network model to a new customized one. The open-source NVIDIA TAO Toolkit, built on TensorFlow and PyTorch, uses the power of transfer learning while simultaneously simplifying the model training process and optimizing the model for inference throughput on practically any platform. The result is an ultra-streamlined workflow. You can adapt your own models or pre-trained models to your own real or synthetic data, and then optimize them for inference throughput, all without needing AI expertise or large training datasets.