Instructions to use JabaleNurAdnan/CS_Checkpoints_Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use JabaleNurAdnan/CS_Checkpoints_Dataset with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://JabaleNurAdnan/CS_Checkpoints_Dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0560742584049e3c483259bff40632e678a7f2be5135fcf1fd7bae0701d6bd5
- Size of remote file:
- 374 kB
- SHA256:
- 2911704947ff46aa5d78049c281469b8b65148658ebfdf83f23bdc7be11d3200
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