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:
- ff7eca53c1c8d74bfc85b880036d4c3ec7b1b0405c4ed38284f4406f902101ee
- Size of remote file:
- 162 kB
- SHA256:
- 9b9be50f7ca78b3e976d05cc9c7f015d34e13002628d68e5285a6ca79220a531
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