Instructions to use prathamrajbhar11/Bijamitra-crop-recommendation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use prathamrajbhar11/Bijamitra-crop-recommendation with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("prathamrajbhar11/Bijamitra-crop-recommendation", "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
🌱 Bijamitra — Crop Recommendation Model
Part of the KissanSahyog agritech platform.
Bijamitra (Hindi/Sanskrit: बीजमित्र) means "seed's friend".
Model Files
| File | Description |
|---|---|
crop_model.pkl |
Multi-class crop classifier |
crop_columns.pkl |
Input feature column order |
label_encoder.pkl |
Crop label encoder |
npk_label_encoder.pkl |
NPK category encoder |
npk_columns.pkl |
NPK feature columns |
Inputs
- Soil:
N,P,K,pH - Climate:
Temperature,Humidity,Rainfall
Output
- Top-3 crop recommendations with confidence scores
Usage
import joblib
import numpy as np
model = joblib.load("crop_model.pkl")
encoder = joblib.load("label_encoder.pkl")
# Example input [N, P, K, pH, Temp, Humid, Rain]
features = np.array([[90, 42, 43, 6.5, 20.8, 82, 202]])
proba = model.predict_proba(features)[0]
# Get top 3 recommendations
top3_idx = np.argsort(proba)[-3:][::-1]
for i in top3_idx:
print(f"{encoder.classes_[i]}: {proba[i]:.2f}")
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