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:
- fe37279d8edc20cdcb7f5a345dba38bf247c7fa369ad2ff8b502995175e4a63e
- Size of remote file:
- 8.4 MB
- SHA256:
- 8b8d0bfec0a3eb23ba171ea271fc5dcd57cdc435105dc07016e767471056abcc
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