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
File size: 499 Bytes
1909d40 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"candidate_rules": [],
"corpus_id": "LF-CORPUS-KERAS-0001",
"description": "Minimal Keras ZIP containing a custom/Lambda-like object reference.",
"expected_rules": [
"LF-KERAS-CUSTOM-OBJECT"
],
"generator": "formats.keras_custom",
"ground_truth": "synthetic-generated",
"must_not_rules": [],
"repo_name": "keras-custom-object",
"repo_type": "model",
"safety": "inert/canary-only",
"schema": 1,
"validation": {
"kind": "inspect",
"target": "model.keras"
}
}
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