Summary
Label Studio is an open-source data labeling platform that provides flexibility for fine-tuning large language models, preparing training data, or validating AI models.
Abstract
Label Studio is a versatile and open-source data labeling platform, which can be installed using pip, brew, git, or Docker. It supports various data types, including images, audio, text, time series, and video, and offers specific computer vision, audio & speech applications, NLP, robots, sensors, IoT devices, and multi-domain applications. The platform provides features like configurable layouts, integration with ML/AI pipelines, ML-assisted labeling, connecting to cloud storage, exploring & understanding data, and supporting multiple projects and users. Label Studio has a growing community and is trusted by many companies.
Bullet Points
- •Open-source data labeling platform for fine-tuning LLMs, preparing training data, or validating AI models
- •Installation options: pip, brew, git, or Docker
- •Supports data types: images, audio, text, time series, and video
- •Specific applications: computer vision, audio & speech, NLP, robots, sensors, IoT devices, and multi-domain
- •Features: configurable layouts, ML integration, cloud storage access, data exploration, and multi-project support
- •Large and growing community, trusted by many companies