Fine-Tuning LLM Using LoRA
Fine-tuning large language models (LLMs) has become an essential technique for adapting pre-trained models to specific tasks. However, full fine-tuning can be computationally expensive and resource-intensive. Low-Rank Adaptation (LoRA) is a technique that significantly reduces the computational overhead while maintaining strong performance. In this article, we will explore fine-tuning LLM using LoRA, its benefits, implementation, … Read more