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 .gitattributes from EnerTEF/Anomaly-Detection-Service: direct link, hf CLI and curl.
- Browser
- Download file 87 Bytes
-
https://huggingface.co/EnerTEF/Anomaly-Detection-Service/resolve/main/.gitattributes
- Command line
-
hf download hf://EnerTEF/Anomaly-Detection-Service/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/EnerTEF/Anomaly-Detection-Service/resolve/main/.gitattributes
87 Bytes
| *.joblib filter=lfs diff=lfs merge=lfs -text | |
| *.csv filter=lfs diff=lfs merge=lfs -text | |