Instructions to use kandinsky-community/kandinsky-2-2-decoder 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 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", 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
Commit History
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Adding `safetensors` variant of this model
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Update README.md
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Create README.md
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vae-to-movq (#2)
- vae -> movq (384c886a0ed26ceba65512645939e08a58bd29bc)67a4915
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Upload model_index.json with huggingface_hub
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Upload unet/config.json with huggingface_hub
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Upload unet/diffusion_pytorch_model.bin with huggingface_hub
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Rename diffusion_pytorch_model.bin to vae/diffusion_pytorch_model.bin
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Upload diffusion_pytorch_model.bin with huggingface_hub
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Upload config.json
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Rename config.json to vae/config.json
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initial commit
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