Model Training & Adaptation
LoRA
Low-rank adaptation
Adapting an AI by learning small additions rather than changing all of its existing learned settings.
Example
A team trains adapters for a specialized writing task.
Why people use it
It can adapt a large AI system while learning a relatively small addition.
What you'll hear
“Train the smaller addition for this task.”
What this means for you
Track adapter and base-AI system compatibility when deploying or sharing results.
Can you control it?
Developer-only
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Does a LoRA adapter contain an entire standalone base AI system?
- Usually not. It typically depends on a compatible base AI system.
- Can different additions serve different jobs?
- Yes. Separate additions can be learned for different tasks, provided they fit the original system.
- Can combining additions cause problems?
- Yes. Their effects can interact, so combining them does not guarantee that each strength is preserved.