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 keras_metadata.pb from fbadine/image-spam-detection-keras2: direct link, hf CLI and curl.
- Browser
- Download file 114 kB
-
https://huggingface.co/fbadine/image-spam-detection-keras2/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://fbadine/image-spam-detection-keras2/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/fbadine/image-spam-detection-keras2/resolve/main/keras_metadata.pb
114 kB
- Xet hash:
- 6940d8cec18bf1cb25fcb5a97334be8f3aad1e24e0595ef2461338d87250164a
- Size of remote file:
- 114 kB
- SHA256:
- 34174cb3b1f54c1a950bffc6f9485d34cec076a6d2e040ff9a1c7fd29dd45651
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