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 rc_car/unet/diffusion_pytorch_model.bin from ImagenHub/DreamBooth-Models: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/ImagenHub/DreamBooth-Models/resolve/main/rc_car/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ImagenHub/DreamBooth-Models/rc_car/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ImagenHub/DreamBooth-Models/resolve/main/rc_car/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- a8d05747330f813bb2c2a56d78a649c6d836c4814490df5c5a79bdf548a1f775
- Size of remote file:
- 3.44 GB
- SHA256:
- d0655d146dab7cf4b5e50025a7c281651ba3d0a3b2f40967da327ec966d61c98
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