Display instructional dataset
Browse and view Hugging Face datasets from a collection
Clean and process datasets
Transfer datasets from HuggingFace to ModelScope
Upload files to a Hugging Face repository
Generate a Parquet file for dataset validation
Create datasets with FAQs and SFT prompts
Manage and label your datasets
Create and manage AI datasets for training models
Annotation Tool
Search narrators and view network connections
Organize and process datasets efficiently
Train a model using custom data
Viewer Embed is a tool designed to help users display and interact with instructional datasets in a structured and user-friendly manner. It provides a seamless way to embed datasets into applications or interfaces, making it easier to visualize and work with data.
• Dataset Visualization: Supports the display of datasets in a readable and organized format.
• Interactive Elements: Allows users to navigate, search, and filter through datasets efficiently.
• Compatibility: Works with various data formats to ensure flexibility and ease of use.
• Customizable Design: Offers options to tailor the appearance of embedded datasets to match different interfaces.
What file formats are supported by Viewer Embed?
Viewer Embed supports a variety of file formats, including CSV, JSON, and Excel files, to ensure compatibility with different dataset sources.
Can Viewer Embed be customized to match my application's design?
Yes, Viewer Embed offers customization options to align its appearance with your application's design, including color schemes and layout adjustments.
Do I need an internet connection to use Viewer Embed?
No, Viewer Embed can be used offline once it has been properly installed and configured in your application.