stp2y

arXiv:2406.01775v1 Announce Type: new Abstract: The advent of large language models (LLMs) has revolutionized natural language processing, enabling unprecedented capabilities in understanding and generating human-like text. However, the computational cost and convergence times associated with fine-tuning these models remain significant challenges. Low-Rank Adaptation (LoRA) has emerged as a promising method to mitigate these issues by introducing efficient fine-tuning techniques with a reduced number of trainable parameters. In this paper, we present OLoRA, an enhancement to the LoRA method that leverages orthonormal matrix initialization through QR decomposition. OLoRA significantly accelerates the convergence of LLM training while preserving the efficiency benefits of…

The rapid advancement of technology has ushered in a wave of innovations that have significantly eased our daily lives and professional responsibilities. Before these developments, the digital landscape lacked the tools necessary to streamline work and business operations. However, with the emergence of intelligent generative AI, the time and energy required for tasks have been substantially reduced. While it's unlikely that AI will render many of us jobless in the foreseeable future, there remains a pressing concern regarding its potential intrusion into our personal and sensitive data if not handled with care. Generative AI, a form of artificial intelligence designed…