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AbstractPhil
/
svae-fresnel-128

Image-to-Image
Transformers
Safetensors
patchsvae
image-reconstruction
svd
geometric-deep-learning
autoencoder
omega-tokens
geolip
custom_code
Model card Files Files and versions
xet
Community

Instructions to use AbstractPhil/svae-fresnel-128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AbstractPhil/svae-fresnel-128 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-to-image", model="AbstractPhil/svae-fresnel-128", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("AbstractPhil/svae-fresnel-128", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
svae-fresnel-128
67.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
AbstractPhil's picture
AbstractPhil
Update README.md
811fb78 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    7.49 kB
    Update README.md 4 months ago
  • config.json
    522 Bytes
    Create config.json 4 months ago
  • configuration_patchsvae.py
    1.79 kB
    Create configuration_patchsvae.py 4 months ago
  • model.safetensors
    67.8 MB
    xet
    Fresnel weights — ep50 MSE=6.681979430373758e-05 4 months ago
  • modeling_patchsvae.py
    11.4 kB
    Update modeling_patchsvae.py 4 months ago
  • test_scale_invariance.py
    13.9 kB
    Create test_scale_invariance.py 4 months ago