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:
- ec60c45ff90ba5b3be1a79bfc8b4ede5c366d5697e8ae658a3fb9062b6d8fb1a
- Size of remote file:
- 162 kB
- SHA256:
- f425fcc6971c1a31a6d0c31a31ba1fa016b01fc8c8cc4c023ab31db371aa8e4e
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