import json
import mlflow
import pandas as pd

logged_model = 'mlruns/1/fa3e620f03e64d888c364827907fb6f5/artifacts/s444409'
loaded_model = mlflow.pyfunc.load_model(logged_model)


with open(f'{logged_model}/input_example.json') as f:
    data = json.load(f)
    input_example = pd.DataFrame(data['inputs'][0])


loaded_model.predict(input_example)