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:
- 0a2ca7bc857b0065cc3a40aaff673ff3c2055ba4aa0a2a2c2059e7b15e4f477f
- Size of remote file:
- 910 MB
- SHA256:
- 9289968b54fc9ccf729e9cfb9619f49d77555badac9bc0784513b9999424ab3d
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