Instructions to use AbstractPhil/SD15-Surge-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AbstractPhil/SD15-Surge-V1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AbstractPhil/SD15-Surge-V1", 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:
- 2a537669a8a32c06d9b08bcf635ada1e97e7b70578e6a19240d2ef9bb9b5dadb
- Size of remote file:
- 168 MB
- SHA256:
- 930b23c3d2c90da51561d6d529bb864e4be106b6ba30eca1fb6af706f6345b33
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