What is LoRA?
Low-Rank Adaptation
It is a technique of making a large artificial intelligence model specialize in a particular subject by updating only a small part of it without changing the entire model.
Overview
LoRA is a method that reduces the massive processing power required to train a massive AI model. You train only a very small layer of the model to add a new style or information to it while preserving its basic capabilities.
How it works
You freeze the weights of the model and just train a small file called LoRA. By installing this file over the main model, you customize it.
Where it is used
It is used in the process of creating personalized visuals or developing special text styles.
Commonly confused with
Mixed with fine-tuning; While fine-tuning can cover the entire model, LoRA is much more lightweight and focused.
Frequently asked questions
Does using LoRA slow down the model?
No, it generally does not cause any performance loss because it is very light.
Can more than one LoRA be installed on a single model?
Yes, different LoRA files can be combined for different features.
Related terms
Related tools
This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →