Building state-of-the-art conversational AI models requires researchers to quickly experiment with novel network architectures. This means going through the complex and time-consuming process of modifying multiple networks and verifying compatibility across inputs, outputs, and data pre-processing layers.
NVIDIA NeMo is a Python toolkit for building, training, and fine-tuning GPU-accelerated conversational AI models using a simple interface. Using NeMo, researchers and developers can build state-of-the-art conversational AI models using easy-to-use application programming interfaces (APIs). NeMo runs mixed precision compute using Tensor Cores in NVIDIA GPUs and can scale up to multiple GPUs easily to deliver the highest training performance possible.
Introduction to NVIDIA NeMo.
NeMo Architecture review.
Building conversational AI models with NeMo.