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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://pratikdoshi/spam-classification-fully-connected") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from pratikdoshi/spam-classification-fully-connected: direct link, hf CLI and curl.
- Browser
- Download file 64.4 kB
-
https://huggingface.co/pratikdoshi/spam-classification-fully-connected/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://pratikdoshi/spam-classification-fully-connected@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/pratikdoshi/spam-classification-fully-connected/resolve/refs%2Fpr%2F1/saved_model.pb
64.4 kB
- Xet hash:
- af60ca28c8c0c50c0dd62335b0de8a4d4d93342444b05a4da23adfa14fd19380
- Size of remote file:
- 64.4 kB
- SHA256:
- 22bd427654dfbf70023671247a5f6136abfccd5d9225d6fff805e6794d57d6b5
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