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Simplifying the LLM journey: From crafting and evaluation to deployment
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Works with any ML library, language & existing code
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Runs the same way in any cloud
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Designed to scale from 1 user to large orgs
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Scales to big data with Apache Spark™
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers several key components:
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MLflow Tracking
Record and query experiments: code, data, config, and results
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MLflow Deployments for LLMs
Interface with cutting-edge LLMs via safe, simple APIs
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MLflow LLM Evaluate
Simplify evaluating LLMs and prompts
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MLflow Projects
Package data science code in a format to reproduce runs on any platform
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MLflow Models
Deploy machine learning models in diverse serving environments
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Model Registry
Store, annotate, discover, and manage models in a central repository
Integrations with:
Organizations using and contributing to MLflow:
To add your organization here, email our user list at mlflow-users@googlegroups.com.
Join the MLflow Community
MLflow is an open source project. To discuss or get help, please join our mailing list mlflow-users@googlegroups.com, or tag your question with #mlflow on Stack Overflow.
We also run a public Slack server for real-time chat.