15 lines
470 B
Python
15 lines
470 B
Python
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import mlflow
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import json
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import numpy as np
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logged_model = '/mlruns/12/1c2b9737c0204b0ca825811c35fb6c64/artifacts/s444409'
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# Load model as a PyFuncModel.
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loaded_model = mlflow.pyfunc.load_model(logged_model)
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with open(f'{logged_model}/input_example.json') as f:
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data = json.load(f)
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input_example = np.array([data['inputs'][0]], dtype=np.float32)
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# Predict on a Pandas DataFrame.
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import pandas as pd
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print(f'Prediction: {loaded_model.predict(input_example)}')
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