Instructions to use gusdelact/flores-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use gusdelact/flores-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("gusdelact/flores-classifier", "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
File size: 682 Bytes
59a00dc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"timestamp": "2026-05-16T02:56:59.506073",
"model_type": "RandomForestClassifier",
"best_params": {
"max_depth": 5,
"max_features": "sqrt",
"min_samples_split": 5,
"n_estimators": 100
},
"best_cv_score": 0.9475348282832468,
"oob_score": 0.9487179487179487,
"cv_accuracy_mean": 0.9485507246376812,
"cv_accuracy_std": 0.04275669357680349,
"n_samples": 117,
"n_features": 4,
"feature_names": [
"SepalLengthCm",
"SepalWidthCm",
"PetalLengthCm",
"PetalWidthCm"
],
"n_classes": 3,
"random_state": 42,
"params": {
"max_depth": "5",
"max_features": "sqrt",
"min_samples_split": "5",
"n_estimators": "100"
}
} |