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:
- 1a792aa5d11f2b936c510dd32fb9d8fbd85168ae0a6f7a30adb55dab3b7c8a6f
- Size of remote file:
- 3.44 GB
- SHA256:
- 5fc6d867c746fa5f04bd3ba6419dce43789c1ed225a5316b9c71647498462a94
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