Label data efficiently with ease
Clean and process datasets
Generate a Parquet file for dataset validation
Manage and orchestrate AI workflows and datasets
Manage and analyze labeled datasets
Rename models in dataset leaderboard
Launch and explore labeled datasets
Display instructional dataset
Create a large, deduplicated dataset for LLM pre-training
Create and manage AI datasets for training models
Generate synthetic datasets for AI training
Explore and edit JSON datasets
Browse and view Hugging Face 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.