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:
- c5847f9893b07ab937f4c98273f9300a199a45bc58fced07db3e1e992f766181
- Size of remote file:
- 162 kB
- SHA256:
- ae3d53031193cb8fa37054a75918ba66ecf715d6f76fcf2bd0c25502540c9b4a
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