worldbank/REaLTabFormer
A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
Need to create synthetic datasets from your existing business data for testing, privacy, or development? This tool takes your raw tabular data, whether it's a single table or multiple related tables, and generates new, realistic synthetic data. It's designed for data scientists, analysts, or developers who work with sensitive or complex datasets and need to simulate real-world data without exposing the originals.
244 stars.
Use this if you need to generate high-quality, realistic synthetic data from your tabular or relational datasets for privacy-preserving analysis, model development, or testing purposes.
Not ideal if you only need basic, anonymized data without preserving complex statistical relationships or if your data isn't structured in tables.
Stars
244
Forks
29
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 04, 2026
Commits (30d)
0
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