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RunDiffusion
/
Juggernaut-X-Hyper

Text-to-Image
Diffusers
English
StableDiffusionXLPipeline
art
people
diffusion
Cinematic
Photography
Landscape
Interior
Food
Car
Wildlife
Architecture
Model card Files Files and versions
xet
Community
3

Instructions to use RunDiffusion/Juggernaut-X-Hyper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use RunDiffusion/Juggernaut-X-Hyper with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-X-Hyper", 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
Juggernaut-X-Hyper / vae
837 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
MorpheusXX0's picture
MorpheusXX0
Adding `diffusers` weights of this model
fd7ff23 verified almost 2 years ago
  • config.json
    607 Bytes
    Adding `diffusers` weights of this model almost 2 years ago
  • diffusion_pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    335 MB
    xet
    Upload 19 files about 2 years ago
  • diffusion_pytorch_model.fp16.safetensors
    167 MB
    xet
    Adding `diffusers` weights of this model almost 2 years ago
  • diffusion_pytorch_model.safetensors
    335 MB
    xet
    Adding `diffusers` weights of this model almost 2 years ago