Instructions to use ava-space/vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ava-space/vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ava-space/vae", 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:
- a18b34077cbd954e626b9a3d0013c1208d65184e58222c542dffe05d7ea33113
- Size of remote file:
- 1.07 GB
- SHA256:
- f89fe7ff56af4d4df9843a6c816b5516e173ec7e92c12dbcdca2bae11612fbb1
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