Instructions to use fbadine/image-spam-detection-keras2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use fbadine/image-spam-detection-keras2 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://fbadine/image-spam-detection-keras2") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from fbadine/image-spam-detection-keras2: direct link, hf CLI and curl.
- Browser
- Download file 3.12 MB
-
https://huggingface.co/fbadine/image-spam-detection-keras2/resolve/main/saved_model.pb
- Command line
-
hf download hf://fbadine/image-spam-detection-keras2/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/fbadine/image-spam-detection-keras2/resolve/main/saved_model.pb
3.12 MB
- Xet hash:
- 7d300c02862743b883a04c63db414839b027f9e2d8df3093a0addd21199e9732
- Size of remote file:
- 3.12 MB
- SHA256:
- 1c7cce92e2a19a4b1b92e35f37b3a8a145428441149cf2c1e09211bb1b4e6cac
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