Instructions to use kaihuac/diffusion-vas-content-completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kaihuac/diffusion-vas-content-completion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kaihuac/diffusion-vas-content-completion", 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:
- 42672cd26047be0429735cddc593a5b6b595ed6813fa93d86ab2785e6aa9b291
- Size of remote file:
- 1.26 GB
- SHA256:
- ae616c24393dd1854372b0639e5541666f7521cbe219669255e865cb7f89466a
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