Instructions to use LayerFault/keras-custom-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use LayerFault/keras-custom-object with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://LayerFault/keras-custom-object") - Notebooks
- Google Colab
- Kaggle
Publish Layerfault synthetic corpus LF-CORPUS-KERAS-0001
Browse files- README.md +1 -1
- SHA256SUMS.json +3 -3
- model.keras +0 -0
README.md
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# keras-custom-object
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> **SECURITY TEST ARTIFACT
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This repository is part of the Layerfault synthetic security corpus.
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It is deliberately constructed to contain security-relevant characteristics for scanner testing.
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# keras-custom-object
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> **SECURITY TEST ARTIFACT: DO NOT USE AS A PRODUCTION MODEL**
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This repository is part of the Layerfault synthetic security corpus.
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It is deliberately constructed to contain security-relevant characteristics for scanner testing.
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SHA256SUMS.json
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"path": "model.keras",
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"sha256": "
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"size": 359
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"path": "README.md",
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"sha256": "3fe6c05b6892c82c62f41d021464d15bfaca5b19998dc3f55ac93620de133ea4",
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"size": 1672
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"path": "model.keras",
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"sha256": "15e8f9b7e76ad1d715e98b05bb5332f4465befc406ffde858bed9af76051de2f",
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"size": 359
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}
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]
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model.keras
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