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:
- 8f739cb4e713a1c917acbf94f1101491d0cd63dbb5560290527bd2104489aec3
- Size of remote file:
- 24.7 MB
- SHA256:
- 4bd5d8781b98a69622cacc84791c2c646a172238e78f20d6d9f0cadd1ba4b1f3
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