LoRA: Low-Rank Adaptation of Large Language Models

In this episode, we dive into LoRA, a groundbreaking technique that makes fine-tuning massive language models like GPT-3 more accessible and efficient. Discover how this method drastically reduces the number of trainable parameters and GPU memory needed, all without adding any extra delay during inference. We'll explore how LoRA freezes the original model and injects small, trainable matrices, achieving results on-par with or even better than full fine-tuning.

There are no comments yet.

Please log in to write the first comment.