NVIDIA Train, Adapt, and Optimize (TAO) is an AI-model-adaptation platform that simplifies and accelerates the creation of enterprise AI applications and services.
By fine-tuning pretrained models with custom data through a UI-based, guided workflow, enterprises can produce highly accurate models in hours rather than months, eliminating the need for large training runs and deep AI expertise.
NVIDIA TAO is an AI-model-adaptation framework that simplifies and accelerates the creation of enterprise AI applications and services, through CLI and GUI based solutions.
- Choose from NVIDIA's library of pretrained models.
- Quickly train, adapt, and optimize models to your unique application.
- Integrate your customized models into your application and deploy.
TAO is an AI-model-adaptation framework that lets enterprise application developers fine-tune pretrained models with custom data to produce highly accurate computer vision, speech, and language understanding models in hours rather than months, eliminating the need for large training runs and deep AI expertise.
Creating an AI/machine learning model from scratch can cost you a lot of time and money.
Transfer learning is a popular technique that can be used to extract learned features from an existing neural network model to a new one.
The NVIDIA TAO Toolkit is a CLI and Jupyter notebook based solution of NVIDIA TAO, that abstracts away the AI/deep learning framework complexity, letting you fine-tune on high-quality NVIDIA pre-trained AI models with only a fraction of the data compared to training from scratch.
The TAO Toolkit also supports 100+ permutations of NVIDIA-optimized model architectures and backbones such as EfficientNet, YOLOv3/v4, RetinaNet, FasterRCNN, UNET, and many more.