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:
- 6999002218a4249abdd0def5173a311ed44e2f284cc9b2f66abd04dc73c03a9f
- Size of remote file:
- 910 MB
- SHA256:
- dff5004bc72c89c005a8dcc1b8943814e59976f525f8d1d2dd15adcff26f380d
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