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bghira
/
pseudo-journey-v2

Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
Model card Files Files and versions
xet
Community
1

Instructions to use bghira/pseudo-journey-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use bghira/pseudo-journey-v2 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("bghira/pseudo-journey-v2", 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
pseudo-journey-v2 / vae
335 MB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 3 commits
ptx0
30000 steps (approx 4 epochs) with terminal SNR on 22k Midjourney 5.1 images plus 7200 real photographs as balance data with complete BLIP captions on all data. BS=4, LR=4e-7 to 1e-8
02b28ff almost 3 years ago
  • config.json
    730 Bytes
    30000 steps (approx 4 epochs) with terminal SNR on 22k Midjourney 5.1 images plus 7200 real photographs as balance data with complete BLIP captions on all data. BS=4, LR=4e-7 to 1e-8 almost 3 years ago
  • diffusion_pytorch_model.safetensors
    335 MB
    xet
    [retrained: based on ptx0/pseudo-journey @ 4000 steps from stable-diffusion-2-1 baseline on 3300 images] + 9500 steps on 22,400 images, polynomial learning rate scheduler, batch size 4, 64 gradient accumulations, FROZEN text encoder, 8bit ADAM, ZERO PLW (no regularization data), followed by 550 steps with unfrozen text encoder and constant LR 1e-8 almost 3 years ago