Visualize dataset distributions with facets
Search and save datasets generated with a LLM in real time
Analyze and compare datasets, upload reports to Hugging Face
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
Parse bilibili bvid to aid / cid
Display competition information and manage submissions
Analyze and visualize Hugging Face model download stats
Explore and analyze RewardBench leaderboard data
Classify breast cancer risk based on cell features
What happened in open-source AI this year, and what’s next?
Display server status information
VLMEvalKit Evaluation Results Collection
Profile a dataset and publish the report on Hugging Face
Facets Overview is a powerful data visualization tool designed to help users better understand their datasets by breaking them down into smaller, manageable parts called facets. It provides insights into how data is distributed across different variables, making it easier to identify patterns, outliers, and relationships within the data.
What libraries or frameworks are required to use Facets Overview?
Facets Overview typically requires TensorFlow and TensorFlow Facets libraries, along with standard data manipulation tools like Pandas.
Can I use Facets Overview with any type of data?
Yes, Facets Overview supports categorical, numerical, and image data, making it versatile for various datasets.
How do I handle large datasets with Facets Overview?
For large datasets, use sampling or data aggregation techniques to improve performance while maintaining meaningful visualizations.
Is Facets Overview suitable for real-time data analysis?
While Facets Overview is primarily designed for offline analysis, it can handle near real-time data with proper setup and optimizations.