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:
- 0be5be1662f49c793eb01c42f95363809327b12527965664dd85c5a3c0e8de4f
- Size of remote file:
- 163 kB
- SHA256:
- 6a37cf2782d5c55dbb97d8d04b9af4ad65675afe7ba6c6c16b8a643e26d7358f
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