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", torch_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:
- bc38c8e1981b80474f9890740631ceb24289f254e292e5ec319e6d16937a9523
- Size of remote file:
- 3.44 GB
- SHA256:
- a266411c5c0aa320252e81e4bddc5cb9557f0e34dc80abac257feef18ac4bb1f
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