Calificación de Usuario
1.0
Puntuación
65
Soporte Gratuito/Prueba
Soportado
Características
1 Características
Última Actualización
feb 05, 2026
¿Qué es label-studio?
Label Studio is an open source data labeling tool that supports multiple projects, users, and data types in one platform. It allows for different types of labeling with various data formats and integrates with M/L backends. It's a flexible platform for fine-tuning LLMs, preparing training data, or validating AI models.
¿Cómo usar label-studio?
Label Studio can be installed via PIP, Brew, Git, or Docker. After installation, you can launch the tool, import data, create projects, and start labeling using customizable tags and templates.
Características Principales
- Support for multiple data types (images, audio, text, video, time series)
- Configurable layouts and templates
- Integration with ML/AI pipelines via Webhooks, Python SDK, and API
- ML-assisted labeling
- Connection to cloud storage (S3, GCP)
- Data Manager with advanced filters
- Multiple projects and users support
Pros & Contras
Sin Datos
Casos de Uso
- Computer Vision: Image classification, object detection, semantic segmentation
- Audio & Speech Applications: Classification, speaker diarization, emotion recognition, audio transcription
- NLP, Documents, Chatbots, Transcripts: Classification, named entity recognition, question answering, sentiment analysis
- Robots, Sensors, IoT Devices: Classification, segmentation, event recognition
- Multi-Domain Applications: Dialogue processing, optical character recognition, time series with reference
- Video: Classification, object tracking, assisted labeling
- GenAI: LLM Fine-Tuning, LLM Evaluations, RAG Evaluation
Grupos de Usuarios
Sin Datos
Precios de label-studio
Plan GratuitoPlan de Suscripción
No detailed pricing information available
Vista Previa de Portada
Características de LABEL-STUDIO
- Funcionalidad de Other AnalysisOther Analysis