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
File size: 251 Bytes
4d6b484 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"_class_name": "KandinskyV22Pipeline",
"_diffusers_version": "0.21.0.dev0",
"movq": [
"diffusers",
"VQModel"
],
"scheduler": [
"diffusers",
"DDIMScheduler"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
]
}
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