Efficiently Fine-tuning Large Language Models with QLoRA: An Introductory Guide
Fine-tuning large language models (LLMs) such as LLaMA and T5 can produce impressive results, but the memory and hardware required for traditional 16-bit fine-tuning can be a major obstacle. A new method called QLoRA (Quantized Low-Rank Adapter) changes that, enabling efficient fine-tuning on large models using much less memory. This article simplifies the core concepts […]