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:
- 2b347ee570eb83f2e68270871260a15deac4870384a2f9ff5d857deb589f1e35
- Size of remote file:
- 162 kB
- SHA256:
- c29fd5ac903083435229d37d0ebb74b011563e8d5f1179d7f1c17887cd56d468
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