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:
- 6ef2df4471dea9a3eeceb60fbab90009a549f42a8ef5064883a56040e85c1214
- Size of remote file:
- 13.4 kB
- SHA256:
- 3f26c7ba933a320bfdae8fa98855fcc0e46ae645b6bc5d2e5716096affeca0a7
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