Instructions to use udg/proge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/proge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/proge", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from udg/proge: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/udg/proge/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://udg/proge/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/udg/proge/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- caa2aa903b839188ec1fc59caa9414946b59ff959e5e7b6c0e95f210e0006b22
- Size of remote file:
- 3.44 GB
- SHA256:
- b148fe0b20de627dc1c3ad10cfb932b67c26fc3ddf0e09e65f9712bf4e79c3fc
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