Instructions to use imaflower/dienbien-coffee-yield with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use imaflower/dienbien-coffee-yield with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("imaflower/dienbien-coffee-yield", "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
| { | |
| "features": [ | |
| "dry_spell_rain_mm", | |
| "flowering_rain_mm", | |
| "fruitdev_rain_mm", | |
| "ripening_rain_mm", | |
| "fruitdev_rain_cv", | |
| "frost_days_sensitive", | |
| "mean_annual_temp_c", | |
| "growing_degree_days", | |
| "mean_sunshine_ripening", | |
| "elevation_m", | |
| "annual_rain_mm" | |
| ], | |
| "model_type": "random_forest" | |
| } |