Run LoRA Run

Run LoRA Run focuses on improving the efficiency and effectiveness of Low-Rank Adaptation (LoRA), a technique for fine-tuning large language models (LLMs) with minimal parameter updates. Current research emphasizes enhancing LoRA's performance in continual learning scenarios, addressing catastrophic forgetting, and improving its application in federated learning and privacy-preserving contexts. These advancements aim to make LLMs more adaptable, resource-efficient, and suitable for deployment on resource-constrained devices while maintaining accuracy, impacting both research and practical applications of LLMs.