Instructions to use ImagenHub/DreamBooth-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ImagenHub/DreamBooth-Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ImagenHub/DreamBooth-Models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download dog2/text_encoder/pytorch_model.bin from ImagenHub/DreamBooth-Models: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/ImagenHub/DreamBooth-Models/resolve/main/dog2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://ImagenHub/DreamBooth-Models/dog2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ImagenHub/DreamBooth-Models/resolve/main/dog2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- baf79ae3acfd2a36ea2a4ea3e39093933ff933882257e099b21b9c491ef81d09
- Size of remote file:
- 492 MB
- SHA256:
- e7ad23b607679e2bd13766ca0de19c76b5acd0b9bf2d6fd730c0e92c5f914a11
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