import mlflow
import numpy as np
import json

logged_model = 'mlrunsArtifact/1/6b2323cf51794581bf1e2f6d060d50f6/artifacts/model'
loaded_model = mlflow.pyfunc.load_model(logged_model)

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

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

print(f'Input: {input_example}')
print(f'Prediction: {loaded_model.predict(input_example)}')