Instructions to use UmerHA/Testing-ConrolNetXS-SDXL-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UmerHA/Testing-ConrolNetXS-SDXL-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-SDXL-depth", torch_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:
- 2afc5298b191e24348968e3e3abe2ea80d7de0b0876f175b446991cbe3669946
- Size of remote file:
- 85 MB
- SHA256:
- bc4da80fe51a3434d71844fb56c77058da1eebc28e62b8bba9439003998fca81
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