Instructions to use gospelgit/Anomaly_Detection_with_Volve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use gospelgit/Anomaly_Detection_with_Volve 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://gospelgit/Anomaly_Detection_with_Volve") - Notebooks
- Google Colab
- Kaggle
Download volve_well_daily.csv from gospelgit/Anomaly_Detection_with_Volve: direct link, hf CLI and curl.
- Browser
- Download file 2.03 MB
-
https://huggingface.co/gospelgit/Anomaly_Detection_with_Volve/resolve/main/volve_well_daily.csv
- Command line
-
hf download hf://gospelgit/Anomaly_Detection_with_Volve/volve_well_daily.csv
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curl -L -o volve_well_daily.csv https://huggingface.co/gospelgit/Anomaly_Detection_with_Volve/resolve/main/volve_well_daily.csv
2.03 MB
File too large to display, you can check the raw version instead.