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:
- 96702bea64913f9e21f9a92cad9a71188849be6f6b28b8e58e8655ced8a1f536
- Size of remote file:
- 162 kB
- SHA256:
- 283d41d9cebd41a859675130ae0fac4384ae6ef5d50593aadb56bfd517246824
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