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Dataset Overview

The Dataset section allows users to explore and manage various datasets that can be used for training, testing, and fine-tuning AI models. Users can browse through a curated list of datasets, filtered by formats such as CSV, JSON, and Text.

Key Features:​

  • Filter by Type: Users can filter datasets by different formats such as CSV, JSON, Text, and JSONL.
  • Most Liked Datasets: This section highlights the most liked datasets, providing quick access to popular resources.
  • Search Datasets: A search bar allows users to quickly locate a specific dataset by name.

How to Use the Dataset Overview:​

  1. Browse Datasets: Scroll through the available datasets or use filters to narrow down by type.
  2. Search: Use the search bar to find a specific dataset by entering keywords.
  3. View Dataset Details: Click on a dataset to view more detailed information, such as its description, format, and size.

Adding New Datasets:​

There are two ways to add a new dataset:

  1. Integration: Select Integration to add a dataset directly from integrated platforms or databases. This allows seamless data flow between your dataset source and the AI model.
  2. Database: Choose Database to import a dataset from a structured database format. This option is ideal for working with relational or other structured datasets.

Key Benefits:​

  • Customizable Datasets: Allows for adding different types of datasets (CSV, JSON, etc.), which are essential for training and testing different models.
  • Most Liked: Easily accessible popular datasets help users pick reliable and high-quality data for their AI models.
tip

Ensure the dataset is clean and well-structured before uploading for the best model performance. Check dataset formats and preview data before fine-tuning or training models.

Example Process:​

  • Dataset Selection: Browse datasets and select one that fits your AI training or testing needs.
  • Adding New Datasets: You can quickly add a new dataset through the New Dataset button, choosing either the Integration or Database options based on your data source.

This screenshot shows a filtered list of datasets, highlighting key dataset details such as the name, format (JSON, CSV, etc.), and size.