GUIDENLP Autolabeling with Quality Assurance 🤖

Celebrating 10,000 GitHub Stars with the Top 10 Label Studio Features

Community

Thank you for your contributions, participation, and support of the Label Studio platform and community!

Label Studio reached a huge milestone on our mission to democratize data labeling and advance data-centric AI! Thanks to the amazing community, we now have 10,000 GitHub stars, only 2.5 years after the initial release! As data scientists and engineers, we created Label Studio to help our peers improve data quality and management, which we believe is the critical factor in achieving better ML/AI outcomes. We’re stoked Label Studio has been so widely adopted and provided value to the greater ML/AI community.

We want to extend a huge thank you to the community for your contributions, support, and participation—from providing feedback and answering questions in slack to reporting bugs and contributing code. Since Label Studio was launched on January 28, 2020, we’ve collectively achieved:

  • 74 contributors
  • 50 releases
  • 1,607 merged pull requests
  • 5M+ downloads

To celebrate, let’s look back at the top 10 milestones of Label Studio development. Over the last 2.5 years, Label Studio gained popularity for being the most flexible data labeling platform, as we’ve added support for more data types, cloud storage, and ML backends, plus management and configuration options through our Python SDK, API, webhooks and configurable UI. We’ve also built Label Studio to scale for unlimited users and projects:

Our journey has just begun. We can’t wait to release more big features this year, and continue iterating with the community on new functionality, best practices, and documentation to support all Label Studio users!

—Nikolai, Max & Michael

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