When training a wan or ltx lora

This discussion covers training custom video LoRAs for Wan and LTX Video models using Low-Rank Adaptation, a fine-tuning technique that customizes outputs for specific subjects, styles, or movements without full model retraining. Wan 2.2 training involves dual transformer models (high noise and low noise) that must be trained separately, requiring powerful GPU setups due to the large architecture. Key hyperparameters like batch size significantly impact training stability, with video LoRAs typically requiring smaller batches (4-8) compared to image-based training due to GPU memory constraints.

Source: r/StableDiffusion | 2026-04-30