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:
- ec3c21b940bd7a7ac5994b2c6e1d6999c241baa76bf92a36bdf8dbee061a2190
- Size of remote file:
- 163 kB
- SHA256:
- 25492f907a47a7158b97404502019147394a0f16095ba4eb6b31d9731e422b7c
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