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:
- 59ba63913e76662198d59b1f8c484ace36dba6a7409480468a1bc96c5c9cb487
- Size of remote file:
- 67.9 MB
- SHA256:
- 63369dc488dfdb303a2e6720ac984ddd63cf059aa443b28a5c8cc1f3965c38b1
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