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:
- 0c3f2561484bfb690096a952d160fbe327041ae22d204489457a8c5c7d24d2b6
- Size of remote file:
- 988 Bytes
- SHA256:
- 01779ab2347be8e591753bc4549de9a4488b45e647b2f7921c9e29c49b9601a9
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