Instructions to use kandinsky-community/kandinsky-2-2-decoder-inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinsky-community/kandinsky-2-2-decoder-inpaint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
#2
by Hooman - opened
README.md
CHANGED
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@@ -39,7 +39,7 @@ pipe_prior.to("cuda")
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prompt = "a hat"
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prior_output = pipe_prior(prompt)
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pipe = KandinskyV22InpaintPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-inpaint", torch_dtype=torch.float16)
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pipe.to("cuda")
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init_image = load_image(
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prompt = "a hat"
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prior_output = pipe_prior(prompt)
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pipe = KandinskyV22InpaintPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder-inpaint", torch_dtype=torch.float16)
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pipe.to("cuda")
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init_image = load_image(
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