Hugging Face and Ray AIR Integration for Scalable Machine Learning

Explore the integration between Hugging Face and Ray AIR in this 31-minute video from Anyscale. Learn how to scale model training and data loading seamlessly for state-of-the-art machine learning in PyTorch, TensorFlow, and JAX. Discover how Ray AIR's Hugging Face integration allows for easy parallelization of Transformers model training across multiple CPUs or GPUs in a Ray cluster, saving time and money. Dive deep into the implementation and API, and understand how to create an end-to-end Hugging Face workflow using Ray AIR, covering data ingest, fine-tuning, hyperparameter optimization, inference, and serving. Gain insights into leveraging the rich Ray ML ecosystem through a common API to enhance your natural language processing, computer vision, audio, and multimodal model development.