Tool dossier

Label Studio

The most flexible data labeling platform for fine-tuning LLMs and preparing training data.

1 sources 27,018 stars Apache-2.0

Product snapshot

How the interface presents itself

Label Studio interface screenshot

Positioning

What this project is really offering

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About

Label Studio is an open-source, multi-type data labeling and annotation tool designed to help you fine-tune large language models (LLMs), prepare training data, and validate AI models. Its flexibility and configurability make it an ideal choice for a wide range of applications, from computer vision to natural language processing (NLP) and beyond. This platform supports various data types, including images, audio, text, time series, and video, making it a versatile tool for data scientists and machine learning engineers alike. Label Studio offers a comprehensive suite of features to streamline your data labeling and annotation tasks, making it an indispensable tool for anyone working with machine learning and AI models.

Highlights

The capabilities most worth remembering

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Image Classification

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Object Detection

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Semantic Segmentation

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Audio Classification

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Speaker Diarization

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Emotion Recognition

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Audio Transcription

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Document Classification

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Named Entity Recognition

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Question Answering

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Sentiment Analysis

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Time Series Classification

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Segmentation

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Event Recognition

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Dialogue Processing

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Optical Character Recognition (OCR)

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Object Tracking

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Assisted Labeling

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ML-assisted Labeling

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Cloud Storage Integration

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Data Management

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Multi-Project Support

Evidence

What backs up the editorial summary