KAIST’s CluSTER method used gradient-based clustering and balanced GPU allocation to train on about 31% of the data while cutting fine-tuning time by up to 69.6% in limited tests.CluSTER Cuts AI Fine-Tuning Time by Choosing What Each GPU Learns
KAIST’s CluSTER method used gradient-based clustering and balanced GPU allocation to train on about 31% of the data whil...
