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:
- 1ea0a4570169aea6e9d01a967df258b9761dc075f62fd88359ea54a0a28be6a7
- Size of remote file:
- 162 kB
- SHA256:
- 09372884276bed061a3573fe540cc06f3fc7aa6c8d8b5e68cd6e42936134cf01
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