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:
- 2b66cea09ddde82d93e1c36d4d8e6274e2f061b022599b1bf237d1fe683eb2e5
- Size of remote file:
- 162 kB
- SHA256:
- e24a937de4ea83ddbcd2641141c3d19ab4b56edd22eaef486b094b826fafd7e7
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