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:
- 09093a2fd9da5ff2c627c010f4866ae3519324db954739b52806ba9520463b3d
- Size of remote file:
- 206 kB
- SHA256:
- 6450e14bc8ad89125b6fdaa9e2e7718d1bc96a55fa214132a211d3b8d4d1e234
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