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Ray Train is a specialized skill for scaling machine learning workloads from a single GPU on a local machine to thousands of nodes in a distributed cluster. It provides a unified API for popular frameworks like PyTorch and Hugging Face, handling complex tasks like GPU allocation, multi-node coordination, fault tolerance, and elastic scaling. By integrating with Ray Tune, it also enables massive-scale hyperparameter optimization and early stopping, making it an essential tool for training large-scale AI models and conducting high-performance AI research efficiently.
