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:
- 0cfda2ef63cecb9287aa5b19a7dffea7a99a249f060550558d32d25145432006
- Size of remote file:
- 20.5 MB
- SHA256:
- cbf6c1616b8ccb0be36070f5171c5f1d210a13caee55d03fe110f8309e4a3917
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