Instructions to use DevBeom/stable-diffusion-class4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DevBeom/stable-diffusion-class4 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-class4", 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:
- ef7f1740de02366df8ab433df7f7be217a3b5104ee0ce51af0723217523b297b
- Size of remote file:
- 3.44 GB
- SHA256:
- 824fb8b81aa7e08209a6d136b9d177fd7bfc200e3e0816c2f853bedb160d755b
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