Instructions to use recoilme/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/temp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recoilme/temp", 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:
- b56481bb7d23372d32c69026b315666ac8da3fb4971d965c80659198c3ea94eb
- Size of remote file:
- 4.64 MB
- SHA256:
- 7b67e9330370a4532352d72944fa428c1c5a9505a0c10c9ae7ebd240e391c4fd
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