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LoRA

Lightweight model fine-tuning method - a small "adapter" instead of retraining everything.

LoRA (Low-Rank Adaptation) is an efficient fine-tuning technique: instead of modifying billions of model parameters, you train a small "adapter" that changes its behavior. The result weighs megabytes instead of gigabytes and trains on a single GPU. LoRA became especially popular in image generation - the community creates thousands of adapters teaching the model specific styles, characters or products. In language models, it's a popular way to cheaply adapt an open model to your own needs.

Related concepts
Fine-tuningOpen-weights modelDiffusion

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