ZenML Blog

The latest news, opinions and technical guides from ZenML.
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ZenML
1 min

CVE-2024-25723: Critical Security Update for ZenML users

A critical security vulnerability has been identified in ZenML versions prior to 0.46.7. This vulnerability potentially allows unauthorized users to take ownership of ZenML accounts through the user activation feature.
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Tutorials
8 mins

Huggingface Model to Sagemaker Endpoint: Automating MLOps with ZenML

Deploying Huggingface models to AWS Sagemaker endpoints typically only requires a few lines of code. However, there's a growing demand to not just deploy, but to seamlessly automate the entire flow from training to production with comprehensive lineage tracking. ZenML adeptly fills this niche, providing an end-to-end MLOps solution for Huggingface users wishing to deploy to Sagemaker.
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mlstacks
3 Mins Read

Introducing mlstacks: a refreshed way to deploy MLOps infrastructure

We released an updated way to deploy MLOps infrastructure, building on the success of the `mlops-stack` repo and its stack recipes. All the new goodies are available via the `mlstacks` Python package.
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ZenML
10 Mins Read

Productionalizing LangChain and LlamaIndex with a ZenML MLOps Pipeline to Help Community Slack Support

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.
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ZenML
5 Mins Read

Build ML Models Faster with ZenML Project Templates

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.
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ZenML
10 Mins Read

ChequeEasy: Banking with Transformers

A winning entry - 3rd prize winner at Month of MLOps 2022 competition. Extraction of metadata from cheques using Transformers and ZenML.
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ZenML
6 Mins Read

Detecting Fraudulent Financial Transactions with ZenML

A winning entry - 2nd prize winner at Month of MLOps 2022 competition.
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ZenML
11 Mins Read

How to train and deploy a machine learning model on AWS Sagemaker with ZenML and BentoML

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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ZenML
24 Mins Read

Transforming Vanilla PyTorch Code into Production Ready ML Pipeline - Without Selling Your Soul

Transform quickstart PyTorch code as a ZenML pipeline and add experiment tracking and secrets manager component.
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