Instructions to use JabaleNurAdnan/CS_Checkpoints_Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use JabaleNurAdnan/CS_Checkpoints_Dataset 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://JabaleNurAdnan/CS_Checkpoints_Dataset") - Notebooks
- Google Colab
- Kaggle
Download CICIDS2017/X_test.npy from JabaleNurAdnan/CS_Checkpoints_Dataset: direct link, hf CLI and curl.
- Browser
- Download file 67.9 MB
-
https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/CICIDS2017/X_test.npy
- Command line
-
hf download hf://JabaleNurAdnan/CS_Checkpoints_Dataset/CICIDS2017/X_test.npy
-
curl -L -o X_test.npy https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/CICIDS2017/X_test.npy
67.9 MB
- Xet hash:
- 59ba63913e76662198d59b1f8c484ace36dba6a7409480468a1bc96c5c9cb487
- Size of remote file:
- 67.9 MB
- SHA256:
- 63369dc488dfdb303a2e6720ac984ddd63cf059aa443b28a5c8cc1f3965c38b1
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