ium_s449288/predict_registry.py

import mlflow
import numpy as np
import json

registry_path = '/mlruns/17/4a8894c60fe34adcb79108c66d7330fc/artifacts/linear-model'
model = mlflow.pyfunc.load_model(registry_path)

with open(f'{registry_path}/input_example.json') as f:
    input_example_data = json.load(f)

input_example = np.array(input_example_data['inputs']).reshape(-1, 8)

print(f'Input example: {input_example}')
print(f'Model prediction: {model.predict(input_example)}')