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:
- 741258065439cf775b4de8cff835877b3b4b11ba165b7227857bcdcb9c644869
- Size of remote file:
- 162 kB
- SHA256:
- 05ca3f3771c2187248a7685adbf6c2b0ae1a0949dd162285e04dabb36cf57ea9
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