Instructions to use gusdelact/pastelerias-linear-regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use gusdelact/pastelerias-linear-regression with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("gusdelact/pastelerias-linear-regression", "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
| { | |
| "model_type": "LinearRegression", | |
| "framework": "scikit-learn", | |
| "target": "Monthly sales", | |
| "feature_order": [ | |
| "Floor space of the shop", | |
| "Distance to the nearest station" | |
| ], | |
| "intercept": 65.32391638894813, | |
| "coefficients": { | |
| "Floor space of the shop": 41.5134782564385, | |
| "Distance to the nearest station": -0.3408826856636193 | |
| }, | |
| "metrics": { | |
| "rmse_loo_cv": 27.016858562584517, | |
| "r2_loo_cv": 0.9042106984038373 | |
| }, | |
| "input_ranges": { | |
| "Floor space of the shop": { | |
| "min": 5, | |
| "max": 10, | |
| "type": "int" | |
| }, | |
| "Distance to the nearest station": { | |
| "min": 0, | |
| "max": 330, | |
| "type": "int" | |
| } | |
| } | |
| } |