In this Issue:

1. Low-Rank Adaptation Fine Tuning(LoRA).

2. The original LoRA paper.

3. The LoRA for Diffusers library.

💡 ML Concept of the Day: LoRA Fine-Tuning and Low-Rank Adaptation Methods

In a new installment of our series about fine-tuning in foundation models, we are going to focus on what can be considered one of the most popular techniques in the space. Low-Rank Adaptation(LoRA) has rapidly emerged as the go-to method in many fine-tuning scenarios. The core ideas behind LoRA as inspirated by techniques such as  principal component analysis (PCA) and singular vector decomposition (SVD) that are used to approximate high dimensional matrices using low-dimensional representations.

Why is this relevant?...