ZBEditor
Label data efficiently with ease
Perform OSINT analysis, fetch URL titles, fine-tune models
Create and validate structured metadata for datasets
Convert a model to Safetensors and open a PR
Explore recent datasets from Hugging Face Hub
Browse a list of machine learning datasets
Evaluate evaluators in Grounded Question Answering
Build datasets using natural language
Upload files to a Hugging Face repository
Organize and invoke AI models with Flow visualization
Organize and process datasets for AI models
Data annotation for Sparky
ZBEditor is a specialized tool designed for dataset creation and management. It allows users to submit or update questions with images for a dataset, making it an essential tool for preparing and refining data for AI training and machine learning applications. Its intuitive interface and advanced features enable efficient dataset curation, ensuring high-quality data for improved model performance.
• Image Integration: Easily add or update images associated with questions in your dataset.
• Question Management: Create, edit, or modify questions to align with your dataset requirements.
• Batch Processing: Handle multiple data entries at once for efficient dataset creation.
• Real-time Preview: Preview how your questions and images will appear in the final dataset.
• Collaboration Support: Work with teams to manage and update datasets seamlessly.
• AI Compatibility: Optimized for integration with AI training pipelines and workflows.
What file formats does ZBEditor support for images?
ZBEditor supports common image formats like JPG, PNG, and BMP. Ensure your images are in one of these formats before uploading.
Can I collaborate with teammates in real-time?
Yes, ZBEditor allows multiple users to collaborate on datasets in real-time, making it ideal for team-based projects.
How do I export my dataset after editing?
After editing, go to the "File" menu and select "Export Dataset." Choose your preferred format, such as CSV or JSON, and save it to your desired location.