DVClive

github.com/treeverse/dvclive AI Data & Analytics Open-source projectOpen source

DVCLive logs and tracks machine learning metrics, parameters, and models with Git or DVC.

github.com/treeverse/dvclive
DVClive homepage screenshot

About DVClive

DVCLive is a Python library for logging machine learning metrics, parameters, models, and other metadata in simple file formats. It is compatible with DVC and stores metrics, parameters, and plots as plain text files that can be versioned with Git or tracked in DVC storage, including saving runs as hidden Git commits.

It provides a Python Live() API with log_param, log_metric, and next_step methods and includes integrations for PyTorch Lightning, Scikit-learn, and Ultralytics YOLO v8. Logged outputs can be compared with dvc exp show and dvc plots, the DVC Extension for VS Code, or DVC Studio, which can show live updates while experiments run.

Key features

  • Log metrics and parameters using the Python Live() API
  • Track training progress with next_step() across steps
  • Store metrics, parameters, and plots as plain text files
  • Save experiments or runs as hidden Git commits
  • Compare experiments with dvc exp show and dvc plots
  • Integrate with PyTorch Lightning, Scikit-learn, and YOLO v8
Best for: Developers who log machine learning metrics and parameters and version results with Git or DVC.
Good for
  • Runs without requiring additional services or servers
  • Stores outputs as plain text files for Git or DVC versioning
  • Open source under the Apache 2.0 license

DVClive at a glance

Type
Open-source project
Pricing
Not confirmed. Check the site
Open source
Yes · Source code
Language
English
Last checked
Oct 5, 2026 · Online when checked
Listed
Oct 5, 2026

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DVClive FAQ

How do I install DVCLive?
Install it with pip install dvclive.
How does DVCLive differ from MLflow, Weights & Biases, or Neptune?
It does not require additional services or servers and stores metrics, parameters, and plots as plain text files versioned by Git or DVC.
How can I compare logged experiments?
Use dvc exp show and dvc plots, the Experiments and Plots views in the DVC Extension for VS Code, or DVC Studio.
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