Instructions to use MWSAH/sdmodels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MWSAH/sdmodels with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MWSAH/sdmodels", 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:
- 4ef8933b73bb190169abd9e7229f9473f23b63fd2d3f845f7f87a2ea667b0a45
- Size of remote file:
- 228 MB
- SHA256:
- 92d01cde90395b9ac90a14522cf158553bf536b4a4a36565a916cfbcec98b8df
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