Instructions to use Wusul/aperturescience with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wusul/aperturescience with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wusul/aperturescience", 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
- Xet hash:
- 57da03e97c120899cc1fa0672d4fe720b272e8c664c908032395a25439341670
- Size of remote file:
- 2.61 GB
- SHA256:
- 921ac6c63b2e0c58f3230578e0a63bc3e8d68fab04b843cbc40f8e3f4b6735d9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.