Buckets:
| # DreamBooth | |
| [DreamBooth](https://huggingface.co/papers/2208.12242) is a method for generating personalized images of a specific instance. It works by fine-tuning the model on 3-5 images of the subject (for example, a cat) that is associated with a unique identifier (`sks cat`). This allows you to use `sks cat` in your prompt to trigger the model to generate images of your cat in different settings, lighting, poses, and styles. | |
| DreamBooth checkpoints are typically a few GBs in size because it contains the full model weights. | |
| Load the DreamBooth checkpoint with [from_pretrained()](/docs/diffusers/pr_14453/en/api/pipelines/overview#diffusers.DiffusionPipeline.from_pretrained) and include the unique identifier in the prompt to activate its generation. | |
| ```py | |
| import torch | |
| from diffusers import AutoPipelineForText2Image | |
| pipeline = AutoPipelineForText2Image.from_pretrained( | |
| "sd-dreambooth-library/herge-style", | |
| dtype=torch.float16 | |
| ).to("cuda") | |
| prompt = "A cute sks herge_style brown bear eating a slice of pizza, stunning color scheme, masterpiece, illustration" | |
| pipeline(prompt).images[0] | |
| ``` | |
Xet Storage Details
- Size:
- 1.12 kB
- Xet hash:
- fda7a8b0df55ad8b6c80601dd4c0ac2c525d23952ea812d8d0ea216c2d279293
·
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