Instructions to use dchan5454/ever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dchan5454/ever with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dchan5454/ever", 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:
- 768e5b7625396f4be7891524c3225e84418b7816d2e9af6436d35571459bdde7
- Size of remote file:
- 335 MB
- SHA256:
- d1642debc84be2a9ab16d4d5b59fa4900b7949881e10db963bc65d396ee6c899
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.