Xiushuang Yi

MoKA:Parameter Efficiency Fine-Tuning via Mixture of Kronecker Product Adaption

With the rapid development of large language models (LLMs), traditional full-parameter fine-tuning methods have become increasingly expensive in terms of computational resources and time costs. For this reason, parameter efficient fine-tuning (PEFT) methods have emerged. Among them, Low-Rank Adaptat…