  --resolution=512 \ Many of the basic and important parameters are described in the Text-to-image training guide, so this guide just focuses on the relevant parameters for InstructPix2Pix: --original_image_column: the original image before the edits are made --edited_image_column: the image after the edits are made --edit_prompt_column: the instructions to edit the image --conditioning_dropout_prob: the dropout probability for the edited image and edit prompts during training which enables classifier-free guidance (CFG) for one or both conditioning inputs  Training script The dataset preprocessing code and training loop are found in the main() function. This is where you’ll make your changes to the training script to adapt it for your own use-case. 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 InstructPix2Pix relevant parts of the script. The script begins by modifing the number of input channels in the first convolutional layer of the UNet to account for InstructPix2Pix’s additional conditioning image:   Copied in_channels = 8