# DreamBooth [DreamBooth](https://huggingface.co/papers/2208.12242) personalizes a pretrained model to a specific subject from a few images (for example, your cat) by fine-tuning the full weights and binding that subject to a unique identifier in the prompt (`sks cat`). You can then generate the subject in new settings, lighting, poses, and styles. DreamBooth checkpoints are typically a few GBs because they contain the full model weights. Load them with [`~DiffusionPipeline.from_pretrained`] and include the unique identifier in the prompt to trigger generation. ```py import torch from diffusers import AutoPipelineForText2Image pipeline = AutoPipelineForText2Image.from_pretrained( "sd-dreambooth-library/herge-style", dtype=torch.float16 ).to("cuda") # or "mps", "xpu", "cpu" prompt = "A cute sks herge_style brown bear eating a slice of pizza, stunning color scheme, masterpiece, illustration" pipeline(prompt).images[0] ```

To train your own checkpoint, see [Train DreamBooth](../training/dreambooth).