The technical value of a revolutionary dataset
SynSQL-2.5M, as the largest text-to-SQL synthetic dataset, is strategically valuable in three dimensions: the data magnitude reaches 2.5 million entries, which is 5-10 times more than similar datasets; it covers 16,000 unique database structures to ensure domain diversity; and each entry contains complete COT (chain of thought) annotations, which provides interpretive guidance for model training. The dataset is generated using an automated pipeline, and through a rigorous quality validation mechanism, its sample accuracy reaches 98.7%. Researchers can conduct cutting-edge research such as migration learning and less-sample learning based on this dataset, and the training scripts provided by the project can directly reproduce the official benchmark results.
This answer comes from the articleOmniSQL: A Model for Transforming Natural Language into High-Quality SQL QueriesThe
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