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:
- 3f965bca50191719d82767628ce498606acc4793e4a3eabd8adf399bd94c84ee
- Size of remote file:
- 374 kB
- SHA256:
- d02b796452ee08d88cac17479833214c5aa0179a10d265f2c1d8244d4a4a6408
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