import mlflow
import numpy as np
import json

regsistry_path = '/mlruns/17/ /artifacts/model' #
model = mlflow.pyfunc.load_model(registry_path) #

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

input_example = np.array() #

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