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:
- c5ce4068fa40a03570e3e3a3bfc4ce869002bf7ca81e20e0e962cca106e66855
- Size of remote file:
- 988 Bytes
- SHA256:
- 32f5654a413f29ef6ef77dd16fce2bb2acb4c1eb7fd3f31b4a5a3f886bc116d3
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