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2e8bf33b0a
This adds model_alias support for native pytorch models. Model aliases can be used in `_infer` or within the inference processor. This way the alias can be atomically changed without down time to another deployed model. Restrictions: - Model alias changes need to be done between two models of the same kind (e.g. pytorch -> pytorch) - Model alias change is not allowed between a model that is deployed to a model that is not - Model alias change is not allowed between a model that deployed AND allocated to a model that is deployed but NOT allocated (not assigned to any nodes). - A deployment cannot be stopped (without supplying the `force` parameter) when the model has a model alias that is used by a pipeline. closes: https://github.com/elastic/elasticsearch/issues/90960 |
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| .. | ||
| clear-trained-model-deployment-cache.asciidoc | ||
| delete-trained-models-aliases.asciidoc | ||
| delete-trained-models.asciidoc | ||
| get-trained-models-stats.asciidoc | ||
| get-trained-models.asciidoc | ||
| index.asciidoc | ||
| infer-trained-model-deployment.asciidoc | ||
| infer-trained-model.asciidoc | ||
| ml-trained-models-apis.asciidoc | ||
| put-trained-model-definition-part.asciidoc | ||
| put-trained-model-vocabulary.asciidoc | ||
| put-trained-models-aliases.asciidoc | ||
| put-trained-models.asciidoc | ||
| start-trained-model-deployment.asciidoc | ||
| stop-trained-model-deployment.asciidoc | ||
| update-trained-model-deployment.asciidoc | ||