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:
- edec87b401ff9f7dff0c570949875a31f6652e4c466459838d5735f44d03fdde
- Size of remote file:
- 9.06 MB
- SHA256:
- 1378c841005e02afa7e219b27ebb8eb4ef64b5b3ccca24c431b553982c6edeea
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