Instructions to use 0bi0n3/Diffusion_test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 0bi0n3/Diffusion_test2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("0bi0n3/Diffusion_test2", 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:
- a8a31605086ba9c79db54abe020d23e75bf17428aeb2e42e95b9eb1f740e8804
- Size of remote file:
- 74.2 MB
- SHA256:
- 5154be6aed35d1b7845f4d67206eef31c296860d039ccbb624e6785feace208c
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