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:
- 9091cf0dbd6000dbbf39354b453c6ee35a80d850994fe1ab04717d6c3671b5a3
- Size of remote file:
- 58 Bytes
- SHA256:
- fe65df1a334d098c351c4805138489c2bab94d5bb96bbcaeb20b8821fe19e37a
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