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:
- e07ad13691e8b884235344446d23297412f8d2a56e3a3f3a437828382d368f18
- Size of remote file:
- 162 kB
- SHA256:
- 0805bd3491bab8a51a93600fc079c347a16913ce4759a7bfccf612a0fbad7246
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