minLoRA re-implements LoRA using PyTorch’s native parametrize utilities, enabling parameter-efficient fine-tuning without modifying model definitions. It supports adding LoRA to linear layers, embeddings, and other modules via a functional API. The library provides utilities for training with LoRA params, merging weights for inference, and loading multiple LoRA adapters for flexible model switching.