Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into an extensive 1-hour 21-minute video tutorial on the distillation of transformer models. Explore various distillation techniques, including layer and width pruning, applied to models like Whisper, Flux, and Minitron. Learn how to initialize student models, compare pre-training and distillation approaches, and understand the differences between cross-entropy loss and KL-divergence. Follow along with a detailed code walk-through for pruning, distillation, and instruction fine-tuning of a SmolLM 135M model to a 99M version. Gain insights into multi-GPU setups, performance monitoring with tensorboard, and dataset selection for instruction fine-tuning. Evaluate distillation performance through various model comparisons and receive valuable tips on pruning approaches, learning rates, and batch sizes. Access additional resources, including slides, research papers, and datasets, to further enhance your understanding of transformer model distillation.