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/y_train.npy from JabaleNurAdnan/CS_Checkpoints_Dataset: direct link, hf CLI and curl.
- Browser
- Download file 1.6 MB
-
https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/Edge_IIoTset/y_train.npy
- Command line
-
hf download hf://JabaleNurAdnan/CS_Checkpoints_Dataset/Edge_IIoTset/y_train.npy
-
curl -L -o y_train.npy https://huggingface.co/JabaleNurAdnan/CS_Checkpoints_Dataset/resolve/main/Edge_IIoTset/y_train.npy
1.6 MB
- Xet hash:
- 9b4b20cce3d5e19b68f77cd18ed29612d59048f32aa9d2b4789e74e09e5f6aeb
- Size of remote file:
- 1.6 MB
- SHA256:
- b2de172aa211607ec1e32b9256bb8485795c528815c0c104a28d555a6b06b4ff
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