Instructions to use hf-internal-testing/tiny-random-kandinsky-v22-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-random-kandinsky-v22-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-random-kandinsky-v22-decoder", 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:
- ed3ce5dcefc49e0f3d1215417b12e8e4dbd30b92af20506be35108a4ae98759c
- Size of remote file:
- 3.56 MB
- SHA256:
- cc4a9badd87f7b7df2f5a0ef7815c76f0e47612b538f5ce399cb96fb2f4efa72
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