In recent times, low-rank adaptation (LoRA) is undoubtedly transforming how developers fine-tune large language models. Instead of retraining hundreds of thousands of parameters, LoRA basically freezes the base model and updates only small and low-rank adapter layers. Thus, it not only cuts down the GPU costs but also preserves accuracy. This certainly makes LoRA one … Continue reading "Low-Rank Adaptation (LoRA): Efficient Fine-Tuning of LLMs" The post Low-Rank Adaptation (LoRA): Efficient...
