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
| { | |
| "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" | |
| } | |
| } | |