Instructions to use DevBeom/stable-diffusion-class2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DevBeom/stable-diffusion-class2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DevBeom/stable-diffusion-class2", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7e0e6b39743cd5f086b66e671c468a088555f689469dc56ce1af09a81ca7c51d
- Size of remote file:
- 3.44 GB
- SHA256:
- 0df96603267644749b9289275ec97ce2b0f7651f2f7c2c7977af9420c1dbd3dd
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