Curate and manage datasets for AI and machine learning
Browse TheBloke models' history
Build datasets using natural language
Convert a model to Safetensors and open a PR
Validate JSONL format for fine-tuning
Explore recent datasets from Hugging Face Hub
Create datasets with FAQs and SFT prompts
Find and view synthetic data pipelines on Hugging Face
Perform OSINT analysis, fetch URL titles, fine-tune models
Browse a list of machine learning datasets
Evaluate evaluators in Grounded Question Answering
Create a domain-specific dataset project
Test is a powerful tool designed to help users curate and manage datasets for AI and machine learning applications. It simplifies the process of creating, organizing, and refining datasets to ensure they are high-quality and ready for use in various projects.
• Dataset Curation: Easily collect, filter, and organize data from multiple sources.
• Data Filtering: Remove noise and irrelevant data to refine your dataset.
• Integration: Seamlessly integrate with popular AI and machine learning platforms.
• Version Control: Track changes and manage different versions of your dataset.
• Collaboration: Share and work on datasets with team members in real-time.
• Export Options: Export datasets in various formats for compatibility with different tools.
What types of data can Test handle?
Test supports a wide range of data formats, including CSV, Excel, JSON, and more, making it versatile for different projects.
Is Test suitable for large-scale datasets?
Yes, Test is designed to handle large-scale datasets with efficient filtering and management capabilities to ensure scalability.
Where can I find more help or resources for Test?
For additional support, visit the official Test documentation or contact the support team via the provided contact information.