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:
- 6de69eb2ead4588a1b0762ff66d52f493d3ea76c708e020e12c1dcc7e7a538a6
- Size of remote file:
- 162 kB
- SHA256:
- 10a1b399c4c22488a129e76f0b02a2ff41fb2b651c0c771ed11eafdff83c4e17
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