test

model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ddea809ff33bc337eb5c7a4976204c44367545ab280cda551bf33c5b3b18ff7b
+size 863

predict.py

@@ -0,0 +1,9 @@
+import joblib
+import sys
+
+model = joblib.load("model.joblib")
+
+value = int(sys.argv[1])
+prediction = model.predict([[value]])[0]
+
+print("odd" if prediction == 1 else "even")

train.py

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+import joblib
+from sklearn.linear_model import LogisticRegression
+import numpy as np
+
+# Training data (toy example)
+X = np.array([[0], [1], [2], [3], [4], [5]])
+y = np.array([0, 1, 0, 1, 0, 1])  # 0 = even, 1 = odd
+
+model = LogisticRegression()
+model.fit(X, y)
+
+# Save model
+joblib.dump(model, "model.joblib")
+
+print("Model trained and saved as model.joblib")