Label Studio 1.8.0 Release

What it does

We’re on a mission to help data scientists build the most accurate AI models! Label Studio is the most popular open source data labeling platform used to fine-tune LLMs and prepare training data. Label any type of data, integrate ML models, and more! 💪🏻

Label Studio documentation: install and upgrade Label Studio with Docker, pip, and anaconda for your machine learning and data science projects.

Install Label Studio on premises or in the cloud. Choose the installation method that works best for your environment: Label Studio is also available an enterprise product , which you can explore instantly through a free trial . You can install Label Studio on a Linux, Windows, or MacOSX machine running Python 3.6 or later. Label Studio expects port 8080 to be open by default. To use a different port, specify it when starting Label Studio. See Start Label Studio . Allocate disk space according to the amount of data you plan to label. As a benchmark, 1 million labeling tasks take up approximately 2.3GB on disk when using the SQLite database. 50GB of disk space is recommended for production…from labelstud.io

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