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README.md

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+---
+license: mit
+tags:
+- crop-recommendation
+- agriculture
+- random-forest
+- classification
+---
+
+# Crop Recommendation Model 🌾
+
+This model recommends the best crop based on soil and weather conditions.
+Inputs required: Nitrogen, Phosphorus, Potassium, Temperature, Humidity, pH, Rainfall.
+
+Trained on Crop Recommendation Dataset.

inference.py

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+import joblib
+import numpy as np
+
+# Load model and label encoder
+model = joblib.load("soil.pkl")
+label_encoder = joblib.load("label_encoder.pkl")
+
+def predict(inputs):
+    """
+    Inputs: List of 7 features [N, P, K, temperature, humidity, ph, rainfall]
+    """
+    input_array = np.array(inputs).reshape(1, -1)
+    prediction = model.predict(input_array)
+    crop = label_encoder.inverse_transform(prediction)
+    return crop[0]

label_encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2c483356146f16bafb2a06d5a2752f59bcad768e83efae06d6a9982e605b4370
+size 830

soil.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5508cefadfad0197f9e5b029eb072fef25ff804a0c23a6a7a427d10a7d97c9b8
+size 3672233