  ----gradient_accumulation_steps=4 Many of the basic and important parameters are described in the Text-to-image training guide, so this guide just focuses on the relevant T2I-Adapter parameters: --pretrained_vae_model_name_or_path: path to a pretrained VAE; the SDXL VAE is known to suffer from numerical instability, so this parameter allows you to specify a better VAE --crops_coords_top_left_h and --crops_coords_top_left_w: height and width coordinates to include in SDXL’s crop coordinate embeddings --conditioning_image_column: the column of the conditioning images in the dataset --proportion_empty_prompts: the proportion of image prompts to replace with empty strings  Training script As with the script parameters, a walkthrough of the training script is provided in the Text-to-image training guide. Instead, this guide takes a look at the T2I-Adapter relevant parts of the script. The training script begins by preparing the dataset. This incudes tokenizing the prompt and applying transforms to the images and conditioning images.   Copied conditioning_image_transforms = transforms.Compose(