Instructions to use alppo/vae-conditioned-diffusion-model_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alppo/vae-conditioned-diffusion-model_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alppo/vae-conditioned-diffusion-model_v2", 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:
- b594d387f1befc0f2fcfe433e86e07893f77489ec67a0712384e08c9fc16aed5
- Size of remote file:
- 472 MB
- SHA256:
- 50b072901f76e43abd3c875b92b8b6f21c329e622a11122a4354e795285e68c6
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