Instructions to use DataScienceProject/CNN_And_ELA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DataScienceProject/CNN_And_ELA 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://DataScienceProject/CNN_And_ELA") - Notebooks
- Google Colab
- Kaggle
Download ELA_CNN_ART_V2.h5 from DataScienceProject/CNN_And_ELA: direct link, hf CLI and curl.
- Browser
- Download file 236 MB
-
https://huggingface.co/DataScienceProject/CNN_And_ELA/resolve/main/ELA_CNN_ART_V2.h5
- Command line
-
hf download hf://DataScienceProject/CNN_And_ELA/ELA_CNN_ART_V2.h5
-
curl -L -o ELA_CNN_ART_V2.h5 https://huggingface.co/DataScienceProject/CNN_And_ELA/resolve/main/ELA_CNN_ART_V2.h5
236 MB
- Xet hash:
- 5f981f92f695cd28cf423c55587f0c21cc385b82fdd9f50e37d6ff2092251e7a
- Size of remote file:
- 236 MB
- SHA256:
- c9b681289e0f151aeb2f52c56dda38c8e1ea89a22ff11e1066c63ad2b3e68fd2
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