Curate and manage datasets for AI and machine learning
Create a large, deduplicated dataset for LLM pre-training
Speech Corpus Creation Tool
Organize and process datasets for AI models
Label data for machine learning models
Convert PDFs to a dataset and upload to Hugging Face
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Generate synthetic datasets for AI training
Organize and process datasets using AI
Save user inputs to datasets on Hugging Face
Manage and label datasets for your projects
Annotation Tool
Test is a specialized tool designed for curating and managing datasets specifically for AI and machine learning applications. It helps users streamline the process of organizing, optimizing, and preparing high-quality datasets, which are essential for training accurate and reliable AI models.
• Dataset Organization: Efficiently categorize and structure your data for easier access and management.
• Data Filtering: Simplify the process of selecting specific data points based on custom criteria.
• Annotation Tools: Add labels and descriptions to data samples to enhance their utility in model training.
• Version Control: Track changes and maintain different versions of your datasets for transparency and collaboration.
• Data Privacy Management: Ensure compliance with data protection regulations by anonymizing or masking sensitive information.
• Collaboration Support: Work with team members on dataset curation through shared access and real-time updates.
• Data Validation: Automatically check for inconsistencies, missing values, and errors in your datasets.
• Integration with AI Pipelines: Seamlessly connect with popular machine learning frameworks for direct model training.
• Multi-Format Support: Handle various data formats, including images, text, audio, and more.
What file formats does Test support?
Test supports a wide range of file formats, including CSV, JSON, TIFF, WAV, and many more, ensuring compatibility with diverse AI applications.
Can I collaborate with team members in real-time?
Yes, Test allows multi-user collaboration, enabling teams to work together on dataset curation and management seamlessly.
Is Test suitable for large datasets?
Absolutely! Test is optimized to handle large-scale datasets efficiently, making it a robust choice for enterprise-level AI projects.