15 lines
428 B
Python
15 lines
428 B
Python
import mlflow
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import numpy as np
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import json
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artifact_path = 'mlruns_s444417/1/169f2bf3d53f4de088c494e889c6e65a/artifacts/model'
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model = mlflow.pyfunc.load_model(artifact_path)
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with open(f'input_example.json') as f:
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input_example_data = json.load(f)
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input_example = np.array(input_example_data['inputs']).reshape(-1, 8)
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print(f'Input example: {input_example}')
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print(f'Model prediction: {model.predict(input_example)}')
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