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Category: Emerging Concepts
Category: Emerging Concepts
LoRA (Low-Rank Adaptation) is a technique for efficiently fine-tuning large AI models by modifying only a small fraction of their parameters.
Instead of updating all model weights, LoRA adds small trainable matrices that adjust the model's behavior. These matrices contain far fewer parameters than the full model.
A 70-billion parameter model might need only 10 million trainable parameters with LoRA.
LoRA makes it practical to customize large models on consumer hardware. What once required massive computational resources now runs on a single GPU.
This democratizes AI customization, letting more people adapt powerful models for specific needs.
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