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:
- 5855ffdf07bf646b90dbb06c05c2bd7a3bcbd74d02eb725f4bd888a5685e6300
- Size of remote file:
- 163 kB
- SHA256:
- 074113e3a3e9f2a2aeb806dea3f516c4ede4e702b99a1f4c222bee21af65f62f
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