Instructions to use DataScienceProject/CNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DataScienceProject/CNN 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") - Notebooks
- Google Colab
- Kaggle
Download best_model_weights/model_fold_2.best.weights.h5.keras from DataScienceProject/CNN: direct link, hf CLI and curl.
- Browser
- Download file 39.3 MB
-
https://huggingface.co/DataScienceProject/CNN/resolve/main/best_model_weights/model_fold_2.best.weights.h5.keras
- Command line
-
hf download hf://DataScienceProject/CNN/best_model_weights/model_fold_2.best.weights.h5.keras
-
curl -L -o model_fold_2.best.weights.h5.keras https://huggingface.co/DataScienceProject/CNN/resolve/main/best_model_weights/model_fold_2.best.weights.h5.keras
39.3 MB
- Xet hash:
- fc5dd1234f606658f35deec79701664ca789423f5159740e74a2d646ac028623
- Size of remote file:
- 39.3 MB
- SHA256:
- 8bd913d026ad213719c7cc8c2cf3a2c11a6c623e915c1df2bd6044e55b372ae0
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