Display instructional dataset
Organize and process datasets using AI
Access NLPre-PL dataset and pre-trained models
Convert and PR models to Safetensors
ReWrite datasets with a text instruction
Display trending datasets from Hugging Face
Support by Parquet, CSV, Jsonl, XLS
Build datasets using natural language
Display trending datasets and spaces
Manage and label your datasets
Upload files to a Hugging Face repository
Save user inputs to datasets on Hugging Face
Browse and extract data from Hugging Face datasets
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.