wehub-resource-sync
29 lines
1013 B
Python
29 lines
1013 B
Python
# This is an example for logging a Python model from code using the
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# mlflow.pyfunc.log_model API. When a path to a valid Python script is submitted to the
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# python_model argument, the model code itself is serialized instead of the model object.
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# Within the targeted script, the model implementation must be defined and set by
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# using the mlflow.models.set_model API.
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import pandas as pd
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import mlflow
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input_example = ["What is the weather like today?"]
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# Specify the path to the model notebook
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model_path = "model_as_code.py"
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print(f"Model path: {model_path}")
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print("Logging model as code using Pyfunc log model API")
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with mlflow.start_run():
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model_info = mlflow.pyfunc.log_model(
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python_model=model_path,
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name="ai-model",
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input_example=input_example,
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)
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print("Loading model using Pyfunc load model API")
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pyfunc_model = mlflow.pyfunc.load_model(model_info.model_uri)
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output = pyfunc_model.predict(pd.DataFrame(input_example, columns=["input"]))
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print(f"Output: {output}")
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