Parameter Efficient Fine-Tuning with Multiple LoRA Adapters for Large Language Models

Parameter Efficient Fine-Tuning with Multiple LoRA Adapters for Large Language Models

Dive deep into Parameter Efficient Fine-Tuning (PEFT) with multiple LoRA adapters in this comprehensive technical video. Explore the intricacies of Low Rank Adaptation (LoRA) and master its various configurations, including all 16 LoRA_config parameters essential for efficient model fine-tuning. Learn to manipulate multiple PEFT adapters by switching between them, activating or deactivating them on pre-trained Large Language Models (LLMs) or Vision Language Models (VLMs). Understand the fundamental concepts of matrix factorization and Singular Value Decomposition (SVD) while discovering how to combine multiple PEFT-LoRA adapters into a single unified adapter for enhanced model performance.