Instructions to use EnD-Diffusers/OsenayanMixPDXL_Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/OsenayanMixPDXL_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("EnD-Diffusers/OsenayanMixPDXL_Diffusers", 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
- Draw Things
- DiffusionBee
- Xet hash:
- e972c159a85adde46d44ae1a5786c7bcb271ad1dbfac7fd5503ed9abf86d07ad
- Size of remote file:
- 5.14 GB
- SHA256:
- 34962740f1b0faf5ee2f584a07ce07f1bb219e83c0aab2862a4eed28784e6268
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.