Create Machine Learning pipelines with ZenML
Evaluate adversarial robustness using generative models
Load AI models and prepare your space
Browse and filter ML model leaderboard data
Convert Hugging Face models to OpenVINO format
Evaluate model predictions with TruLens
View and submit language model evaluations
Request model evaluation on COCO val 2017 dataset
Merge Lora adapters with a base model
Find and download models from Hugging Face
Calculate memory needed to train AI models
Calculate GPU requirements for running LLMs
Convert Hugging Face model repo to Safetensors
Zenml Server is a tool designed to streamline the creation and management of Machine Learning (ML) pipelines. It allows users to build, deploy, and scale their ML workflows efficiently, making it easier to collaborate and manage complex ML projects.
• Pipeline Management: Create and manage end-to-end ML workflows with ease.
• Integration: Seamlessly integrate with popular ML frameworks and tools.
• Extensibility: Customize workflows to fit specific project requirements.
• Collaboration: Support for team-based workflows and shared resources.
• Version Control: Track changes and manage different versions of your pipelines.
• Performance Optimization: Tools to optimize and monitor pipeline performance.
What is Zenml Server used for?
Zenml Server is primarily used for managing and optimizing Machine Learning pipelines, enabling teams to streamline their ML workflows and improve collaboration.
How do I install Zenml Server?
Zenml Server can be installed using Docker. Follow the installation guide on the official ZenML documentation for step-by-step instructions.
Can Zenml Server handle large-scale ML workflows?
Yes, Zenml Server is designed to scale with your needs and can handle large-scale ML workflows efficiently.