A small set of parameters added to a frozen base model to customize behavior without full fine-tuning; includes techniques like LoRA. Adapters are often the deliverable in custom AI projects, so ownership, portability, and confidentiality terms are often stated explicitly. Frequently used as a way to provide organization-specific capabilities without creating full separate base models.
See: Fine-tuning; LoRA (Low-Rank Adaptation); Parameter-efficient fine-tuning