Microsoft AI Researchers Developed a New Improved Framework ResLoRA for Low-Rank Adaptation (LoRA)

Large language models (LLMs) with hundreds of billions of parameters have significantly improved performance on various tasks. Fine-tuning LLMs on specific datasets enhances performance compared to prompting during inference but incurs high costs due to parameter volume. Low-rank adaptation (LoRA) is a popular parameter-efficient fine-tuning method for LLMs, yet updating LoRA block weights efficiently is […]

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