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dreamcomputing
/
ProtoNaut

Text-to-Image
Diffusers
Safetensors
English
StableDiffusionXLPipeline
art
people
diffusion
Cinematic
Photography
Landscape
Interior
Food
Car
Wildlife
Architecture
Model card Files Files and versions
xet
Community
1

Instructions to use dreamcomputing/ProtoNaut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use dreamcomputing/ProtoNaut with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("dreamcomputing/ProtoNaut", 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
ProtoNaut
15.7 GB
Ctrl+K
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  • 1 contributor
History: 10 commits
Chris
Update README.md
f362e5c verified about 1 year ago
  • scheduler
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  • text_encoder
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  • text_encoder_2
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  • tokenizer
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  • tokenizer_2
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  • unet
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  • vae
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  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    454 Bytes
    Update README.md about 1 year ago
  • model_index.json
    712 Bytes
    Upload 18 files about 1 year ago