5 дней назад · Mosaic AI Model Serving provides a unified interface to deploy, govern, and query AI models for real-time and batch inference. Manage model serving... · Migrate to Model Serving · Foundation Model APIs |
Effortless batch inference. Model Serving enables efficient AI inference on large datasets, supporting all data types and models in a serverless environment. |
Model serving with Azure Databricks - Microsoft Learn learn.microsoft.com › azure › machine-learning
5 дней назад · Model Serving provides a highly available and low-latency service for deploying models. The service automatically scales up or down to meet ... |
30 окт. 2024 г. · Mosaic AI Model Serving is Databricks' unified interface to deploy, govern, and query AI and ML models. Each model you serve is available as a ... Model Serving · Foundation Model APIs · Batch inference · Deploy custom models |
30 окт. 2024 г. · This article describes how to create model serving endpoints that serve custom models using Databricks Model Serving. |
Databricks Model Serving provides a unified interface to deploy, govern, and query AI models, making it easier to handle the complexities of model serving. Each ... |
31 окт. 2024 г. · This article provides the basic steps for deploying and querying a custom model, that is a traditional ML model, using Mosaic AI Model Serving. |
Model Serving limits and regions | Databricks on AWS docs.databricks.com › machine-learning › mod...
5 дней назад · This article summarizes the limitations and region availability for Mosaic AI Model Serving and supported endpoint types. |
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