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:
- dc63a12ac33946818025d5736faa4a46a671585e1add436bbbae4c703800b20c
- Size of remote file:
- 162 kB
- SHA256:
- 0f62ed66bd785a3e79a19ba85e1d53408df248b58955e02f74455d60ad6d5f96
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