Instructions to use Araeynn/e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Araeynn/e with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Araeynn/e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f236b0fe3d072a979cb301bef3d8cd7fdb6b6808e694da4b33cdaef30f53bb3
- Size of remote file:
- 27.9 kB
- SHA256:
- 47084dc7622501dbbee20f4033e7844c48eef560b4044394aa2951f50487547e
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