Instructions to use borgsid/borgsidlukee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use borgsid/borgsidlukee with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("borgsid/borgsidlukee", 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:
- 7db091e2b3ffb8a8279c59de0aa386e30148ac74b300454c710b7cdb473f679b
- Size of remote file:
- 3.46 GB
- SHA256:
- 6d8059e9d299921a323cfa28560552847f7fb9bfd0956891c773ad71d24cd9a8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.