Buckets:
| # DreamBooth | |
| [DreamBooth](https://huggingface.co/papers/2208.12242) mempersonalisasi model pretrained ke subjek tertentu dari beberapa gambar (misalnya, kucing Anda) dengan fine-tuning seluruh bobot dan mengaitkan subjek tersebut ke pengidentifikasi unik dalam prompt (`sks cat`). Anda kemudian dapat menghasilkan subjek tersebut dalam pengaturan, pencahayaan, pose, dan gaya baru. | |
| Checkpoint DreamBooth biasanya berukuran beberapa GB karena berisi bobot model lengkap. Muat dengan [from_pretrained()](/docs/diffusers/main/id/api/pipelines/overview#diffusers.DiffusionPipeline.from_pretrained) dan sertakan pengenal unik dalam prompt untuk memicu generasi. | |
| ```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] | |
| ``` | |
| Untuk melatih checkpoint Anda sendiri, lihat [Melatih DreamBooth](../training/dreambooth). | |
Xet Storage Details
- Size:
- 1.14 kB
- Xet hash:
- c3c9052ab4cc9aedec3761841302e97c92ccc6a05252356a0e23a7eddfbdc925
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.