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docs/en/stack/ml/anomaly-detection/anomaly-detection-scale.asciidoc
@@ -65,7 +65,7 @@ size of a {ml} node. Creating {ml-jobs} with model memory limits larger than the
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maximum node size can support is not allowed, as autoscaling cannot add a node
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big enough to run the job. On a self-managed deployment, you can set
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`xpack.ml.max_model_memory_limit` according to the available resources of the
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-{ml} node. This prevents you from you creating jobs with model memory limits too
+{ml} node. This prevents you from creating jobs with model memory limits too
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high to open in your cluster.
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[discrete]
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