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sst12345
/
CoRe2

Text-to-Image
Diffusers
English
inference-enhanced algorithm
efficiency
effectiveness
generalization
weak-to-strong guidance
Model card Files Files and versions
xet
Community

Instructions to use sst12345/CoRe2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use sst12345/CoRe2 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("sst12345/CoRe2", 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 Settings
  • Draw Things
  • DiffusionBee
CoRe2
4.92 GB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 5 commits
Klayand's picture
Klayand
update README.md
193a505 over 1 year ago
  • diffusion_pipeline
    repo init over 1 year ago
  • weights
    first version of CoRe^2 over 1 year ago
  • .gitattributes
    1.52 kB
    first version of CoRe^2 over 1 year ago
  • LICENSE
    11.4 kB
    Initial commit over 1 year ago
  • README.md
    2.81 kB
    update README.md over 1 year ago
  • sample_img.py
    9.54 kB
    first version of CoRe^2 over 1 year ago