Instructions to use kandinsky-community/kandinsky-2-2-controlnet-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinsky-community/kandinsky-2-2-controlnet-depth 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-controlnet-depth", 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
Adding `safetensors` variant of this model
#7
by SFconvertbot - opened
movq/diffusion_pytorch_model.safetensors
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oid sha256:43a5860fea195a7116f2471396c5cc9535fade9b63c4857d8a192ffd924b7002
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size 271380364
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unet/diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6549f8c8471357ed8ed6b700a80ffdd8fe45bd5b54f4c486d7f81ac9fe5f343b
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size 5013798992
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