Instructions to use dzhov/sd-class-jellyfish-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dzhov/sd-class-jellyfish-64 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dzhov/sd-class-jellyfish-64", 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:
- f437fcaf03a68790993a852bd4128dea98df4593bd5aa6f413a7d5aa6c10a158
- Size of remote file:
- 455 MB
- SHA256:
- 363e01b184f7ed624ce1b3946507fde962cd90c388ee92173118567d32017d53
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