AnandInguva commented on code in PR #23218:
URL: https://github.com/apache/beam/pull/23218#discussion_r971406025
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website/www/site/content/en/documentation/sdks/python-machine-learning.md:
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@@ -83,6 +83,14 @@ You need to provide a path to a file that contains the
pickled Scikit-learn mode
`model_uri=<path_to_pickled_file>` and `model_file_type: <ModelFileType>`,
where you can specify
`ModelFileType.PICKLE` or `ModelFileType.JOBLIB`, depending on how the
model was serialized.
+### Use custom models
+
+In fact, the RunInference API is designed flexibly to allow you to use any
custom machine learning models. You only need to create your own `ModelHandler`
or `KeyedModelHandler` to handle how the ML models are loaded from a location
that the pipeline can access and how to use these models to run the inference.
+
+A simple example can be found in [this
notebook](https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/run_custom_inference.ipynb).
+The `load_model` method is created to load the models using a popular `spaCy`
package while `run_inference` shows how to run the inference on a batch of
examples.
Review Comment:
```suggestion
The `load_model` method shows how to load the model using a popular `spaCy`
package while `run_inference` shows how to run the inference on a batch of
examples.
```
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