Instructions to use pratikdoshi/spam-classification-fully-connected with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use pratikdoshi/spam-classification-fully-connected with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://pratikdoshi/spam-classification-fully-connected") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af60ca28c8c0c50c0dd62335b0de8a4d4d93342444b05a4da23adfa14fd19380
- Size of remote file:
- 64.4 kB
- SHA256:
- 22bd427654dfbf70023671247a5f6136abfccd5d9225d6fff805e6794d57d6b5
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