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sales-forecast-model
dev02chandan/sales-forecast-model
sales-forecast-model is a tabular regression model from dev02chandan. Use it for the tabular regression task on the model card, and read the license before you ship it in a product. It is set up for scikit-learn. The card lists the license as apache-2.0.
Task: Predict ProductStoreSalesTotal from product and store attributes. Data: dev02chandan/sales-forecast-dataset (raw/SuperKart.csv with processed train/test under processed/). Model: GradientBoostingRegressor select…
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Updated Dec 15, 2025
Repo size
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.pkl238 KB · 99%
At a glance
- Task
- Tabular Regression
- Library
- scikit-learn
- License
- apache-2.0
- Access
- Public
- Created
- Oct 11, 2025
- Updated
- Dec 15, 2025
- SHA
- 234284a6
Model card
From the Hugging Face model README
Sales Forecast Model (GBR)
Task: Predict Product_Store_Sales_Total from product and store attributes.
Data: dev02chandan/sales-forecast-dataset (raw/SuperKart.csv with processed train/test under processed/).
Model: GradientBoostingRegressor selected via GroupKFold CV on Store_Id.
Test Metrics
- CV RMSE: 1157.1346565946897
- RMSE: 1600.05837632221
- MAE: 1405.5687461646362
- MAPE: 27.069205177956633
- sMAPE: 32.25248697544593
Usage
from huggingface_hub import hf_hub_download
import joblib, pandas as pd
pkl_path = hf_hub_download(repo_id="dev02chandan/sales-forecast-model", filename="model.pkl", repo_type="model")
model = joblib.load(pkl_path)
# X must contain the same columns used in training (one-hot is inside the pipeline)
# Example:
# X = pd.DataFrame([...])
# y_pred = model.predict(X)
- Task
- Tabular Regression
- Library
- scikit-learn
- License
- apache-2.0
- Created
- Oct 11, 2025
- Updated
- Dec 15, 2025