Large Language Models, Machine Learning, Deep Learning, Data Science, Technology.
would involve ( d² ) parameters. However, with ( B ) and ( A ) of sizes ( d x r ) and ( r x d ) respectively, the total number of parameters reduces to ( 2dr ), which is much smaller when ( r << d ). The reduction in the number of trainable parameters, as achieved through the Low-Rank Adaptation