Explore the innovative LoRA (Low-Rank Adaptation) technique in this 30-minute video from Unify. Discover how LoRA enables efficient fine-tuning of large language models by freezing pre-trained weights and introducing trainable low-rank matrix decompositions into transformer layers. Learn about the significant reduction in trainable parameters required for task-specific adaptation and its implications for improving machine learning models. Gain insights from the original research paper and access additional resources, including AI research newsletters, blogs on AI deployment, and various platforms to connect with the Unify community.
LoRA Explained - Efficient Fine-Tuning of Large Language Models
Overview
Syllabus
LoRA Explained
Taught by
Unify
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