Instructions to use mkiani/keras-python3.10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use mkiani/keras-python3.10 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-python3.10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07aba226edaefa44e5d9c04fc908622e5a07f4700fe02319951bade743f2b36a
- Size of remote file:
- 425 kB
- SHA256:
- 74b6cda2529000246cc59e8534e6c1bafb8b2a192783550a3f6258f32d37703c
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