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:
- 05612dab50b93103632ae8aabad6e9712e9c0982e326136060c253bc9ad81c3f
- Size of remote file:
- 2.89 MB
- SHA256:
- f75b3a46cb6fe3bff07e066a7bd04aa3e4adc3415bf03d2fd004032574b7f5aa
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