Instructions to use maxpmx/ddpm_val with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maxpmx/ddpm_val with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maxpmx/ddpm_val", 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:
- c73587fbb4457e70a971100acd8c04e24bdb3f1169014aa6c75afa81bbf6d596
- Size of remote file:
- 910 MB
- SHA256:
- f91049e37e86bb5325ff3e28e8cdaadb105861a70aa4c036b24076e3f784aeda
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