Parameter-efficient fine-tuning

Adapting a frozen base model by training only small added weight matrices (e.g. LoRA adapters) rather than all parameters, cutting the compute and storage cost of customization.

grounded in: LoRA/PEFT as an established open-weights adaptation technology, connected to the system's open-weights + local-first + vllm inference stack and the 'cheaper/faster model' trend theme.

Connected concepts

Open-weight LLMs, Quantization, Model migration, vLLM / PagedAttention, Federated Learning