Instructions to use kaizerkam/sd-class-comics-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kaizerkam/sd-class-comics-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("kaizerkam/sd-class-comics-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:
- 288ac794bc30f5251146e38a5b036f37800d203f7e5d805727b61a0bc7146d60
- Size of remote file:
- 74.3 MB
- SHA256:
- ce2cf688a0ff3aa1570474dde130c8ee1c01264e15349bd6eb378b162f418af1
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