ModelServingDataset 類別 參考 意見反應 表示建立模型型 DataDriftDetector 物件時,在內部使用的資料集。 以模型為基礎的 DataDriftDetector 可讓您計算模型訓練資料集與其評分資料集之間的資料漂移。 若要建立以模型為基礎的 DataDriftDetector,請使用 <xref:azureml.datadrift.DataDriftDetector.create_from_model> ...
この記事では、Azure DatabricksModel Servingが利用されているサービング エンドポイントに、複数のモデルを提供する方法について説明します。 要件 Model Serving エンドポイント作成の要件を参照してください。 モデル サービング エンドポイントのアクセスの制御オプション...
Learn how to deploy MLflow models as REST API endpoints with Azure Databricks Legacy MLflow Model Serving.
PUT /api/2.0/serving-endpoints/modelA-Production/config { "served_entities":[ { "entity_name":"model-A", "entity_version":"2", // New Production model version "workload_size":"Small", "scale_to_zero_enabled":true }, ], } 将MosaicML 推理工作流迁移到模型服务 本部分提供有关如何将...
Why does AzureML PromptFlow logging show <REDACTED> for flow run results? I'm working with an AzureML PromptFlow deployment for a project and have noticed that recent logs in the "Online deployment log" now show <REDACTED>: [2024-12-10 11:32:22 +0000][pfserving-app][INFO] - Validati...
When deploying models at scale on an Azure Container Service cluster, we’ve built a hosting infrastructure optimized for model serving, that handles automatic scaling of containers, as well as efficiently routing requests to available containers. Deployed models and services can be monitored through ...
We also announced that managed MLflow is generally available on Azure Databricks and will use Azure Machine Learning to track the full ML lifecycle. The combination of Azure Databricks and Azure Machine Learning makes Azure the best cloud for machine learning. Databricks open sourced Databricks Delta...
As a general rule, I favor dedicated cache roles for housing regions, because I don’t want to load down a role that’s serving user traffic with all of the traffic for cache fetches related to a given region. The bottom row in Figure 6 depicts using the co-located style of caching ...
PagedAttention: vLLM: Easy, Fast, and Cheap LLM Serving with PagedAttention, 24x Faster LLM InferenceLink Open AI Plugin and function calling ChatGPT Plugin ChatGPT Function calling Under the hood, functions are injected into the system message in a syntax the model has been trained on. This...
Diagram-2: Azure Single Subscription workspace model Multi-Subscription workspace model In this model, core infrastructure and Citrix infrastructure are in separate subscriptions to manage the scalability in large deployments. Often enterprise deployments with multi-region infrastructure designs are ...