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:
- fbe9344fde089150d8c5b5a4827024c167e6464cb5e2e7b8495cd99b012548a6
- Size of remote file:
- 482 kB
- SHA256:
- 5cc97d74d114899a0e011c3d9be4681bc2597c22c73a396f6974e6cde9d10e1a
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