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:
- aef1a18c027b8ab9d287de16a01bb94cb551075bb96f68a0438c74a48ffcac46
- Size of remote file:
- 162 kB
- SHA256:
- 6ab7c43d1d85b6f7187c4f764f86febdacd449493dfd13ed6edb3f4145b8d772
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