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 Batch_Normalization_Added.keras from idk100/intel-image-classification-cnn-comparison: direct link, hf CLI and curl.
- Browser
- Download file 18.8 MB
-
https://huggingface.co/idk100/intel-image-classification-cnn-comparison/resolve/main/Batch_Normalization_Added.keras
- Command line
-
hf download hf://idk100/intel-image-classification-cnn-comparison/Batch_Normalization_Added.keras
-
curl -L -o Batch_Normalization_Added.keras https://huggingface.co/idk100/intel-image-classification-cnn-comparison/resolve/main/Batch_Normalization_Added.keras
18.8 MB
- Xet hash:
- fb4c1b933fecd02bc725081dc564d76978f862f23e8306bc27ad91773b96d633
- Size of remote file:
- 18.8 MB
- SHA256:
- 4aa030a1fed89471cc54c0306abd723ec63c80119e409c04a70a5d1af8d08659
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