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output/openapi/elasticsearch-openapi.json

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output/openapi/elasticsearch-serverless-openapi.json

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output/schema/schema.json

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specification/inference/put/PutRequest.ts

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@@ -26,7 +26,7 @@ import { Id } from '@_types/common'
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* Create an inference endpoint.
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* When you create an inference endpoint, the associated machine learning model is automatically deployed if it is not already running.
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* After creating the endpoint, wait for the model deployment to complete before using it.
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* To verify the deployment status, use the get trained model statistics API.
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* To verify the deployment status, use the get trained model statistics API.
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* Look for `"state": "fully_allocated"` in the response and ensure that the `"allocation_count"` matches the `"target_allocation_count"`.
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* Avoid creating multiple endpoints for the same model unless required, as each endpoint consumes significant resources.
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*

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