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:
- 0c0145753a4ee334778a5e13639af420353cbff2304f6012d5446a24c581998f
- Size of remote file:
- 3.44 GB
- SHA256:
- 5585f2a9c7faa23bfe716a2c236fb9a39a0fe9748c5740eae473dd5ef8598195
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.