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:
- db86824cee37670d36c2aafa23dd182331ad5aa5182bbc593a980eba7f2871bb
- Size of remote file:
- 163 kB
- SHA256:
- 93279b279b3e12bdfb1904924ae07fce0f0b3058548c17a72ac1f9b2d7a77f2a
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