Instructions to use ericyoc/the_applied_ai_universe_coding_guide with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ericyoc/the_applied_ai_universe_coding_guide with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ericyoc/the_applied_ai_universe_coding_guide") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43948056f3787162873dc32c940d8dff492902c727a32e3e8e297618c26865b2
- Size of remote file:
- 1.82 MB
- SHA256:
- 069098f1b844df7d6e946f5aa9f8bc88230fc6bb147b71f98c89b9161650ea6f
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