Instructions to use ItsMaxNorm/diffusion-p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ItsMaxNorm/diffusion-p with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ItsMaxNorm/diffusion-p", 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:
- 476fdeec5cf459df07c7edc2d128da2009e0b39ef9d9618e7131229f30f96140
- Size of remote file:
- 3.44 GB
- SHA256:
- 8a2f400beb16ec6473860b4e7597fb4c040f3fc4f1f5a7f4fa81927d6eeb20ea
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