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:
- 21924f60f96ec43bc3602df7071ff2d30e485706f74fe72077c92e1cfc201ee7
- Size of remote file:
- 910 MB
- SHA256:
- b70d14103f696f7ae95d3a345d8a2d901bd7b618f1ae94c1b3a3ac1f6d0b5135
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