Instructions to use idk100/intel-image-classification-cnn-comparison with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use idk100/intel-image-classification-cnn-comparison 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://idk100/intel-image-classification-cnn-comparison") - Notebooks
- Google Colab
- Kaggle
Download Base_CNN_Model.keras from idk100/intel-image-classification-cnn-comparison: direct link, hf CLI and curl.
- Browser
- Download file 18.7 MB
-
https://huggingface.co/idk100/intel-image-classification-cnn-comparison/resolve/main/Base_CNN_Model.keras
- Command line
-
hf download hf://idk100/intel-image-classification-cnn-comparison/Base_CNN_Model.keras
-
curl -L -o Base_CNN_Model.keras https://huggingface.co/idk100/intel-image-classification-cnn-comparison/resolve/main/Base_CNN_Model.keras
18.7 MB
- Xet hash:
- 82fc9df1d4011049c382a9e2e62085e4793b5eafbdc3e8b45b7b2f498bb307bf
- Size of remote file:
- 18.7 MB
- SHA256:
- 16ee6d344d57ad4a971bb2ed79f6c7e4e669e0787108d84411c86cf991c863a2
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