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:
- 9b4b20cce3d5e19b68f77cd18ed29612d59048f32aa9d2b4789e74e09e5f6aeb
- Size of remote file:
- 1.6 MB
- SHA256:
- b2de172aa211607ec1e32b9256bb8485795c528815c0c104a28d555a6b06b4ff
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