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:
- d56b29b4cfdc44f8d490fa6b3bdebe10810032aa89f420d8f51046c2087c74ee
- Size of remote file:
- 36.4 kB
- SHA256:
- a872b18896ee238ddfdf40d7b667a6f024cae3f4739a63a68095d750d8f0a692
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