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Yntec
/
ReVive

Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Anime
Illustration
Cartoon
Fantasy
Sci Fi
stable-diffusion
stable-diffusion-diffusers
s6yx
Model card Files Files and versions
xet
Community
6

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

  • Libraries
  • Diffusers

    How to use Yntec/ReVive with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("Yntec/ReVive", 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
ReVive / vae
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  • 1 contributor
History: 2 commits
Yntec's picture
Yntec
Adding `diffusers` weights of this model (#2)
230771e verified over 1 year ago
  • config.json
    653 Bytes
    Adding `diffusers` weights of this model (#1) over 1 year ago
  • diffusion_pytorch_model.fp16.safetensors
    335 MB
    xet
    Adding `diffusers` weights of this model (#2) over 1 year ago
  • diffusion_pytorch_model.safetensors
    335 MB
    xet
    Adding `diffusers` weights of this model (#2) over 1 year ago