Use Cases

Real-world applications

Research and Experimentation

Researchers can organize and run deep learning experiments with clear separation of model logic and engineering code.

Scalable Production Training

Machine learning engineers can deploy models on distributed hardware such as GPUs and TPUs without changing code.