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:
- a7d3596dec3414c21b299d74bd3f6add4a395eb215734d2982f394e3e0ee9815
- Size of remote file:
- 316 kB
- SHA256:
- 0f96071a994c1e0679c130c659db59613b65f65a4c2d635fe1f79a09446efca2
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