Data Collection
Collect data from multiple data sources with DataMate
User Guide
DataMate feature usage guides
This guide introduces how to use each feature module of DataMate.
DataMate provides comprehensive data processing solutions for large models, covering data collection, management, cleaning, annotation, synthesis, evaluation, and the full process.
Feature Modules
- Data Collection - Collect data from multiple data sources
- Data Management - Manage datasets and files
- Data Cleaning - Clean and preprocess data
- Data Annotation - Data annotation and quality control
- Data Synthesis - Data augmentation based on large models
- Data Evaluation - Data quality evaluation
- Knowledge Base - RAG knowledge base construction
- Operator Market - Data processing operator management
- Pipeline Orchestration - Visual workflow orchestration
- Agent Chat - AI intelligent assistant
Typical Use Cases
Model Fine-tuning Scenario
1. Data Collection → 2. Data Management → 3. Data Cleaning → 4. Data Annotation
↓
5. Data Evaluation → 6. Export Training Data
RAG Application Scenario
1. Upload Documents → 2. Vectorization Index → 3. Knowledge Base Management
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4. Agent Chat (Knowledge Base Q&A)
Data Augmentation Scenario
1. Prepare Raw Data → 2. Create Instruction Template → 3. Data Synthesis
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4. Quality Evaluation → 5. Export Augmented Data
Quick Links
- Quick Start - Deployment and installation
- API Reference - API documentation
- Developer Guide - Architecture and development
Data Management
Manage datasets and files with DataMate
Data Cleaning
Clean and preprocess data with DataMate
Data Annotation
Perform data annotation with DataMate
Data Synthesis
Use large models for data augmentation and synthesis
Data Evaluation
Evaluate data quality with DataMate
Knowledge Base Management
Build and manage RAG knowledge bases with DataMate
Operator Market
Manage and use DataMate operators
Pipeline Orchestration
Visual workflow orchestration with DataMate
Agent Chat
Use DataMate Agent for intelligent conversation
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