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:
- 9cf07ea61eaf51b079faf8fdd32a819d76ebec3a2d3ab347767fa896f8f5fd17
- Size of remote file:
- 910 MB
- SHA256:
- cb8c2b3c500c15c7ce7539812dc6d35159ed38ec111446d3a9b6edef62d9a80e
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