A comprehensive overview of lessons learned from the world's largest database of LLMOps case studies (457 entries as of January 2025), examining how companies implement and deploy LLMs in production. Through nine thematic blog posts covering everything from RAG implementations to security concerns, this article synthesizes key patterns and anti-patterns in production GenAI deployments, offering practical insights for technical teams building LLM-powered applications.
We decided to explore how the emerging technologies around Large Language Models (LLMs) could seamlessly fit into ZenML's MLOps workflows and standards. We created and deployed a Slack bot to provide community support.
ZenNews is a tool powered by ZenML that can automate the summarization of news sources and save you time and effort while providing you with the information you need.
Getting started with your ML project work is easier than ever with Project Templates, a new way to generate scaffolding and a skeleton project structure based on best practices.
Learn how to use ZenML pipelines and BentoML to easily deploy machine learning models, be it on local or cloud environments. We will show you how to train a model using ZenML, package it with BentoML, and deploy it to a local machine or cloud provider. By the end of this post, you will have a better understanding of how to streamline the deployment of your machine learning models using ZenML and BentoML.
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