18 lines
362 B
Python
18 lines
362 B
Python
|
import mlflow
|
||
|
|
import numpy as np
|
||
|
|
import json
|
||
|
|
|
||
|
|
artifact_path = 'mlruns/1//artifacts/model' #
|
||
|
|
model = mlflow.pyfunc.load_model(artifact_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)}')
|
||
|
|
|
||
|
|
|
||
|
|
|