Tabular Regression
Scikit-learn
Joblib
GradientBoostingRegressor
demand-forecasting
retail
xgboost
gcc
agentic-commerce
ocg-dubai
gulf-retail
e-commerce
Instructions to use GencoDiv/ramadan-demand-forecaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use GencoDiv/ramadan-demand-forecaster with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("GencoDiv/ramadan-demand-forecaster", "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
- Xet hash:
- 9f07e00b1de35e81d2636ac59e669e5b1775bb6dfeae4e3eb21c0411fd6401ca
- Size of remote file:
- 1.76 MB
- SHA256:
- 69bef2bf5c0f86a0819e3a66afcf5a196fa3335ba8e17d87e3b6e31a7c69401a
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