Annotation Tool
Access NLPre-PL dataset and pre-trained models
Browse a list of machine learning datasets
Create datasets with FAQs and SFT prompts
Browse and extract data from Hugging Face datasets
Perform OSINT analysis, fetch URL titles, fine-tune models
Explore and edit JSON datasets
Upload files to a Hugging Face repository
Review and rate queries
Create a large, deduplicated dataset for LLM pre-training
Create a report in BoAmps format
Build datasets using natural language
Build datasets and workflows using AI models
Math is a powerful annotation tool designed for dataset creation and management. It simplifies the process of configuring and managing datasets for machine learning applications. With Math, users can easily annotate, organize, and prepare data, making it an essential tool for data scientists, machine learning engineers, and researchers.
• Dataset Configuration: Easily set up and manage datasets for various machine learning tasks.
• Advanced Annotation Tools: Annotate data with precision using customizable labels and templates.
• Integration Capabilities: Seamlessly integrate with popular machine learning frameworks.
• Collaboration Features: Work with teams to annotate and manage datasets efficiently.
• Version Control: Track changes and maintain different versions of datasets.
1. What is Math used for?
Math is primarily used for annotating and managing datasets for machine learning workflows. It helps streamline the data preparation process.
2. Do I need technical expertise to use Math?
No, Math is designed to be user-friendly. However, basic knowledge of machine learning workflows and dataset preparation is helpful.
3. Can Math integrate with other tools?
Yes, Math supports integration with popular machine learning frameworks and tools, making it versatile for different workflows.