mages = [image.convert("RGB") for image in examples[image_column]]
    examples["clip_pixel_values"] = image_processor(images, return_tensors="pt").pixel_values
    examples["text_input_ids"], examples["text_mask"] = tokenize_captions(examples)
    return examples Finally, the training loop converts the input images into latents, adds noise to the image embeddings, and makes a prediction:   Copied model_pred = prior(
    noisy_latents,
    time