Unconditional Image Generation
Diffusers
Safetensors
English
priming
image-generation
class-conditional
one-step
imagenet
Instructions to use BiliSakura/Priming-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/Priming-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/Priming-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "golden retriever" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download .gitignore from BiliSakura/Priming-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 33 Bytes
-
https://huggingface.co/BiliSakura/Priming-diffusers/resolve/main/.gitignore
- Command line
-
hf download hf://BiliSakura/Priming-diffusers/.gitignore
-
curl -L -o .gitignore https://huggingface.co/BiliSakura/Priming-diffusers/resolve/main/.gitignore
33 Bytes
| __pycache__/ | |
| *.py[cod] | |
| .DS_Store | |