Instructions to use Poomz/loreitup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Poomz/loreitup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Poomz/loreitup", 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
- Xet hash:
- 9313e24065fb99accd2b4f12e161a9c71783a8db195b6dc1726f941de5cd05af
- Size of remote file:
- 3 GB
- SHA256:
- 2dda994f0d26fc681ff763121eea321fa936a47bddf87178d4622e639df17603
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.