Instructions to use Falah/sdworldlandmarks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Falah/sdworldlandmarks with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Falah/sdworldlandmarks", 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:
- 2db5a6e7d83b1f0bd21ad714a02adb69b2737fe810308022c6f4d64d634d1065
- Size of remote file:
- 246 MB
- SHA256:
- b0fe3469cb54eaac80ffeafc40aba9875c2ad5a538b22c85c4333b6b9e33f296
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.