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 Edge_IIoTset/X_test.npy from JabaleNurAdnan/CS_Checkpoints_Dataset: direct link, hf CLI and curl.
- Browser
- Download file 8.4 MB
-
https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/Edge_IIoTset/X_test.npy
- Command line
-
hf download hf://JabaleNurAdnan/CS_Checkpoints_Dataset/Edge_IIoTset/X_test.npy
-
curl -L -o X_test.npy https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/Edge_IIoTset/X_test.npy
8.4 MB
- Xet hash:
- fe37279d8edc20cdcb7f5a345dba38bf247c7fa369ad2ff8b502995175e4a63e
- Size of remote file:
- 8.4 MB
- SHA256:
- 8b8d0bfec0a3eb23ba171ea271fc5dcd57cdc435105dc07016e767471056abcc
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