7 Approaches to Efficient LLM Training on Limited Hardware

Engineers can train 7B to 70B parameter LLMs on dual 24 GB consumer GPUs using QLoRA with 4-bit NormalFloat quantization, Double Quantization, and DoRA adapters. GaLore projects gradients via SVD to cut optimizer state memory, while ZeRO-3 host offload shards parameters across VRAM and CPU RAM.