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Label Studio is tested with the latest version of Google Chrome and is expected to work in the latest versions of: PostgreSQL version 11.5 or SQLite version 3.35 or higher. for example, t3.large or t3.xlarge on Amazon AWS.įor more on using Label Studio at scale and labeling performance, see Start Label Studio. Use a minimum of 8GB RAM, but 16GB RAM is recommended. 50GB of disk space is recommended for production instances. As a benchmark, 1 million labeling tasks take up approximately 2.3GB on disk when using the SQLite database. Server requirementsĪllocate disk space according to the amount of data you plan to label. To use a different port, specify it when starting Label Studio. Label Studio expects port 8080 to be open by default.
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You can install Label Studio on a Linux, Windows, or MacOSX machine running Python 3.6 or later.
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Label Studio is also available an enterprise product, which you can explore instantly through a free trial. Choose the installation method that works best for your environment: However, most of the time, restarting the program fixes the problem.Install Label Studio on premises or in the cloud. Some programming languages may cause a few issues due to the real-time compilation. Not only that, but the app also provides access to other coding languages besides Python. You can adjust it depending on your or your organization's needs. Moreover, it also employs a number of data sources to guarantee redundancy, including SQL, NoSQL, and Flat Files.Īnaconda is modular in nature. It updates changes in real-time and is compatible with most cloud services, such as Google Drive.

The app prioritizes group functionality, allowing you to coordinate with multiple teams when working on one data project together. Not only that, but it also works to simplify the process of working together on large batches of information.Īnother core benefit of using Anaconda is its enhanced interdepartmental collaboration. It enables organizations to successfully secure, interpret, scale, and store data critical to their operation. As mentioned, it is great for managing all kinds of information and provides users an environment that facilitates access to heavy amounts of data.
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Functions and usabilityĪnaconda is an enterprise-level software bundle that provides a host of innovative options to the end-user. More importantly, it provides warnings if dependencies already exist. What makes Conda different from Python's PIP is that it checks for the requirement of the dependencies before installing them. It also facilitates the creation and loading with equal speed and even allows easy environment switching. This feature quickly installs the dependencies along with the frequent updates. You will also find the Conda package, which is a virtual environment manager. This makes it easy for users to launch applications and manage packages and environments without using the command-line commands. In it, you will find the Anaconda Navigator, which is the graphical alternative to the command-line interface. Upon completion, the app provides you with more than 1,500 packages in its distribution. Installing the app is simple as it only requires you to follow the instructions from the wizard setup. However, despite that, programmers still choose this program for fast installation and ease of use. It offers all the required packaged involved in data science at once. It focuses on the distribution of R and Python programming languages and aims at simplifying the data management and deployment of the mentioned languages. Anaconda is primarily developed to support data science and machine learning tasks.
