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:
- 6e11a6bcfec42d1ea2bda1ec306f540173370ef40f880d32c94414c7a19c2316
- Size of remote file:
- 163 kB
- SHA256:
- ec9827bfc61ae1a34f1ec44279aa243adbb42c127d6e6709c1823ad58a1a39cf
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