Tabular Classification
Scikit-learn
Joblib
English
timeseries
detection
anomaly-detection
energy
battery-storage
vrfb
gaussian-mixture-model
one-class-svm
Instructions to use EnerTEF/Anomaly-Detection-Service with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use EnerTEF/Anomaly-Detection-Service with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("EnerTEF/Anomaly-Detection-Service", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download model.joblib from EnerTEF/Anomaly-Detection-Service: direct link, hf CLI and curl.
- Browser
- Download file 14.7 kB
-
https://huggingface.co/EnerTEF/Anomaly-Detection-Service/resolve/main/model.joblib
- Command line
-
hf download hf://EnerTEF/Anomaly-Detection-Service/model.joblib
-
curl -L -o model.joblib https://huggingface.co/EnerTEF/Anomaly-Detection-Service/resolve/main/model.joblib
14.7 kB
- Xet hash:
- cb4a979e03b6537fd893fda3d5b0370cead995096b2010d0fc66abdce612aaa4
- Size of remote file:
- 14.7 kB
- SHA256:
- 856b572bad800fb8107c164f20fc5280a84b2c1d345af551c54c17a6fceec6a1
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