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[8.18][DOCS] Adds model_id to the default endpoint docs. (elastic#124089)
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docs/reference/inference/inference-apis.asciidoc

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@@ -58,8 +58,10 @@ For more information about adaptive allocations and resources, refer to the {ml-
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Your {es} deployment contains preconfigured {infer} endpoints which makes them easier to use when defining `semantic_text` fields or using {infer} processors.
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The following list contains the default {infer} endpoints listed by `inference_id`:
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* `.elser-2-elasticsearch`: uses the {ml-docs}/ml-nlp-elser.html[ELSER] built-in trained model for `sparse_embedding` tasks (recommended for English language texts)
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* `.multilingual-e5-small-elasticsearch`: uses the {ml-docs}/ml-nlp-e5.html[E5] built-in trained model for `text_embedding` tasks (recommended for non-English language texts)
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* `.elser-2-elasticsearch`: uses the {ml-docs}/ml-nlp-elser.html[ELSER] built-in trained model for `sparse_embedding` tasks (recommended for English language tex).
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The `model_id` is `.elser_model_2_linux-x86_64`.
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* `.multilingual-e5-small-elasticsearch`: uses the {ml-docs}/ml-nlp-e5.html[E5] built-in trained model for `text_embedding` tasks (recommended for non-English language texts).
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The `model_id` is `.e5_model_2_linux-x86_64`.
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Use the `inference_id` of the endpoint in a <<semantic-text,`semantic_text`>> field definition or when creating an <<inference-processor,{infer} processor>>.
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The API call will automatically download and deploy the model which might take a couple of minutes.

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