nt_checkpointing, gradient_accumulation_steps, and mixed_precision to reduce memory-usage and speedup training. You can reduce your memory-usage even more by enabling memory-efficient attention with xFormers and bitsandbytes’ 8-bit optimizer. This guide will explore the train_lcm_distill_sd_wds.py script to help you become more familiar with it, and how you can adapt it for your own use-case. Before running the script, make sure you install the