Label data efficiently with ease
Access NLPre-PL dataset and pre-trained models
Create Reddit dataset
Display trending datasets and spaces
Browse and search datasets
Explore datasets on a Nomic Atlas map
Explore and edit JSON datasets
Generate dataset for machine learning
Create and manage AI datasets for training models
Save user inputs to datasets on Hugging Face
Create and validate structured metadata for datasets
Review and rate queries
A collection of parsers for LLM benchmark datasets
LabelStudio is an open-source tool designed for efficient data labeling and dataset creation. It simplifies the process of annotating data for machine learning models, supporting various data types such as text, images, and audio. With its intuitive interface and customizable workflows, LabelStudio is a popular choice for data scientists and annotators.
• Support for multiple data types: Label text, images, audio, and more in a single platform.
• Customizable templates: Define your own labeling templates to fit specific project requirements.
• Collaboration features: Work with teams and manage annotations efficiently.
• Integration capabilities: Easily integrate with machine learning pipelines and workflows.
• Open-source flexibility: Customize and extend the tool to meet your needs.
What is LabelStudio primarily used for?
LabelStudio is primarily used for annotating and labeling data to prepare it for machine learning model training.
Can LabelStudio handle different types of data?
Yes, LabelStudio supports labeling for text, images, audio, and other data types, making it versatile for various projects.
Where can I download LabelStudio?
LabelStudio is open-source and can be downloaded from its official GitHub repository or used via Docker.