LORA: Low-Rank Adaptation of Large Language Models

Introduction:
This article explains LoRA [1], a parameter-efficient method for fine-tuning models to solve downstream tasks and the paper’s underlying motivation. While the methods in LoRA should be generally applicable to fine-tune any model for any downstream tasks, the focus of this paper is on text generation tasks using large-language models (LLMs). Several real-world problems e.g., summarization, topic classification, Natural language to SQL, can be framed as text generation problems. Each problem can be specified by a set of N …

fine-tuning gpt large language models llm lora