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:
- 39116720471be3bea667e06207bca488bcb181456463041376dce09d6b99df89
- Size of remote file:
- 400 kB
- SHA256:
- 42af700c752ec7571f27d152b3744d92f714b2d64a04efda085b6fac8edd4b28
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