Instructions to use UmerHA/Testing-ConrolNetXS-SD2.1-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UmerHA/Testing-ConrolNetXS-SD2.1-depth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("UmerHA/Testing-ConrolNetXS-SD2.1-depth", 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:
- afec34836248676434f58b2be77989a0de4915e650ecc44ff83324686c3da2ec
- Size of remote file:
- 28.4 MB
- SHA256:
- e089448b94dd9aa678cb63499dfa4517d9e5903f00f7302b65df3c3f63132c93
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.