Instructions to use mkiani/keras-python3.9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use mkiani/keras-python3.9 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://mkiani/keras-python3.9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9a3ae9005ddfef1dec2051fbd8bf1808c1c60c23707ef2d6e29a9d5b5623a9c
- Size of remote file:
- 425 kB
- SHA256:
- a640516ceb58cb03f9303711d7da988a50cf313395642d1f85abb1bf62d75406
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