Instructions to use ChristianTeroerde/modelscan-nested-lambda-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ChristianTeroerde/modelscan-nested-lambda-poc with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ChristianTeroerde/modelscan-nested-lambda-poc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65767b005f3b5647f64cb2fa565bd46430b348faa968f75cbc7b616217109a2d
- Size of remote file:
- 9.22 kB
- SHA256:
- 0258b0b256e023d809b4bb95321da46feb82395258e009506d128ba0de13e821
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