Was ist LoRA (Low-Rank Adaptation)

Definition

LoRA (Low-Rank Adaptation) is an efficient fine-tuning method that freezes the original weights of a pre-trained model, training only a small set of additional, mathematically compressed parameters instead.

Explanation

LoRA dramatically reduces the storage and computational demands of fine-tuning language models. This is because it requires adjusting only a few million parameters, rather than billions. This empowers even smaller B2B and SaaS companies to fine-tune large models on their own servers or cost-effective cloud instances for highly specialized tasks. Furthermore, LoRA modules are dynamically swappable. This means a single base model can be loaded with various small LoRA weights to perform diverse functions – from generating emails and analyzing customer conversations to reviewing contracts. Consequently, this enables the integration of highly customized AI solutions into existing sales and CRM systems with extreme flexibility, cost-efficiency, and scalability.