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Dataset Creation
Trending Repos

Trending Repos

Display trending datasets from Hugging Face

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What is Trending Repos ?

Trending Repos is a tool designed to display trending datasets from the Hugging Face ecosystem. It provides an intuitive interface to explore and discover new datasets, making it easier for data enthusiasts and researchers to stay updated with the latest resources in the field of AI and machine learning.

Features

  • Display trending datasets: Showcases popular and widely-used datasets from Hugging Face.
  • Customization options: Allows users to filter datasets by time range, popularity, and other criteria.
  • User-friendly interface: Provides an easy-to-navigate platform for exploring datasets.
  • Real-time updates: Ensures users have access to the latest trending datasets.
  • Integration with Hugging Face Hub: Directly connects to the Hugging Face ecosystem for seamless access.

How to use Trending Repos ?

  1. Install the Trending Repos application from the appropriate source (e.g., GitHub, PyPI).
  2. Launch the application to view a curated list of trending datasets.
  3. Use the filtering options to narrow down datasets by specific criteria (e.g., time range, popularity).
  4. Click on a dataset to view detailed information, including its description, usage statistics, and access links.
  5. Access the dataset directly from Hugging Face Hub using the provided links.

Frequently Asked Questions

What datasets are displayed in Trending Repos?
Trending Repos displays datasets from the Hugging Face Hub, focusing on those that are currently popular or trending within the AI and machine learning communities.

How are datasets ranked or ordered?
Datasets are ranked based on factors such as the number of downloads, likes, and usage within the Hugging Face ecosystem. The ranking can also be customized based on user preferences.

Can I access datasets directly from Trending Repos?
Yes, Trending Repos provides direct links to datasets on Hugging Face Hub, allowing users to access and download them seamlessly.

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