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Top 11 Model Deployment and Serving Tools

Analytics Vidhya

This is where model deployment and serving tools come into play. By […] The post Top 11 Model Deployment and Serving Tools appeared first on Analytics Vidhya. Introduction Machine learning models hold immense potential, but they need to be effectively integrated into real-world applications to unlock their true value.

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Announcing the General Availability of Databricks Feature Serving

databricks

Today, we are excited to announce the general availability of Feature Serving. Features play a pivotal role in AI Applications, typically requiring considerable.

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Introducing Mixtral 8x7B with Databricks Model Serving

databricks

Today, Databricks is excited to announce support for Mixtral 8x7B in Model Serving. Mixtral 8x7B is a sparse Mixture of Experts (MoE) open.

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Accelerate GenAI App Development with New Updates to Databricks Model Serving

databricks

Last year, we launched foundation model support in Databricks Model Serving to enable enterprises to build secure and custom GenAI apps on a.

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2021 State of Analytics: Why Users Demand Better

The expectation to do more with their data becomes a moving target for them and the applications that serve them. As organizations become more data driven, their analytics requirements grow. To stand up to the challenge, applications must evolve to accommodate their users and ensure their success. But what do users really want?

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Deploy Private LLMs using Databricks Model Serving

databricks

We are excited to announce public preview of GPU and LLM optimization support for Databricks Model Serving! With this launch, you can deploy.

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TensorFlow Serving: Deploying Deep Learning Models Just Got Easier!

Analytics Vidhya

Learn about deploying deep learning models using TensorFlow Serving How to handle post-deployment challenges like swapping between different versions of models using TensorFlow Serving. The post TensorFlow Serving: Deploying Deep Learning Models Just Got Easier! appeared first on Analytics Vidhya.