[GitHub] [beam] andres-vv commented on a diff in pull request #25083: Multi language/runinference example

["andres-vv (via GitHub)" <gi...@apache.org>]

andres-vv commented on code in PR #25083:
URL: https://github.com/apache/beam/pull/25083#discussion_r1126384992


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website/www/site/content/en/documentation/ml/overview.md:
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@@ -105,3 +105,4 @@ You can find examples of end-to-end AI/ML pipelines for several use cases:
 * [Anomaly Detection in Beam](/documentation/ml/anomaly-detection): Demonstrates how to set up an anomaly detection pipeline that reads text from Pub/Sub in real time and then detects anomalies using a trained HDBSCAN clustering model with the RunInference API.
 * [Large Language Model Inference in Beam](/documentation/ml/large-language-modeling): Demonstrates a pipeline that uses RunInference to perform translation with the T5 language model which contains 11 billion parameters.
 * [Per Entity Training in Beam](/documentation/ml/per-entity-training): Demonstrates a pipeline that trains a Decision Tree Classifier per education level for predicting if the salary of a person is >= 50k.
+* [Cross-language RunInference in Beam](/documentation/ml/multi-language-inference): Demonstrates a cross-language java pipeline that uses a custom python transform to do preprocessing, postprocessing, and inference.

Review Comment:
   Okay, thanks for the heads-up!



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