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:
- 18dbadbc680fac020ae18564a3c325682218c2fe61ca4949e825992b8cda8adc
- Size of remote file:
- 988 Bytes
- SHA256:
- a749d7364a7687e861260a2dbd568bc0f0ca6417f6fad25d379c584c51f5573e
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