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Duplicated from  kandinsky-community/kandinsky-2-2-decoder

cjwalch
/
kandinsky-endpoint

Text-to-Image
Diffusers
Safetensors
KandinskyV22Pipeline
kandinsky
Model card Files Files and versions
xet
Community

Instructions to use cjwalch/kandinsky-endpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use cjwalch/kandinsky-endpoint with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("cjwalch/kandinsky-endpoint", 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
  • Draw Things
  • DiffusionBee
kandinsky-endpoint
10.6 GB
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  • 2 contributors
History: 3 commits
cjwalch's picture
cjwalch
Upload handler.py
0ab38e4 verified about 1 year ago
  • movq
    Duplicate from kandinsky-community/kandinsky-2-2-decoder over 1 year ago
  • scheduler
    Duplicate from kandinsky-community/kandinsky-2-2-decoder over 1 year ago
  • unet
    Duplicate from kandinsky-community/kandinsky-2-2-decoder over 1 year ago
  • .gitattributes
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  • README.md
    7.34 kB
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  • handler.py
    2.59 kB
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  • model_index.json
    250 Bytes
    Duplicate from kandinsky-community/kandinsky-2-2-decoder over 1 year ago
  • requirements.txt
    110 Bytes
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