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:
- f99df3a4e0cb51d203000d33bcb28e6a8cd59f4c7c8933d0d56c542badd4e33f
- Size of remote file:
- 910 MB
- SHA256:
- 7282573f6bf37eae501c4b8402137ab2c94cc3441fa89529f1f2a391e2ea117b
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