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:
- 6a5c90023a38980752f8e60891abee0c791f61c5badea0a76dee4f7a14babb12
- Size of remote file:
- 4.12 MB
- SHA256:
- 778bcaea9b7f74379dacc0f6bea251f832f49f7a583aebb3f127d954eacbe2b0
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