Instructions to use Vijish/depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vijish/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("Vijish/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:
- e3f449f55f7f9370145a2c9a419b1ab2de39677901b81dcce611ec614d581100
- Size of remote file:
- 1.45 GB
- SHA256:
- 2a74732cd1fac0ea5be714354f9dff7cbf25469488f4777a2857282857d88c66
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