Instructions to use ckpt/controlavideo-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/controlavideo-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("ckpt/controlavideo-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:
- c8059e23f770b243232947f7f5a9bd9f240b2ce756152f993163585985f99572
- Size of remote file:
- 1.32 GB
- SHA256:
- 206005278c033b855998d9cc9077553f1788ed43173f5e3d6e902e5fa52070d5
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