datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SQaLe-text-to-SQL-dataset
🧮 SQALE: A Large-Scale Semi-Synthetic Dataset
SQALE is a large-scale, semi-synthetic Text-to-SQL dataset grounded in real-world database schemas.
It was designed to push the boundaries of natural language to SQL generation, combining realistic schema diversity, complex query structures, and linguistically varied natural language questions.
The dataset was introduced in the paper SQaLe: A Large Text-to-SQL Corpus Grounded in Real Schemas. The code for the generation pipeline of this… See the full description on the dataset page: https://huggingface.co/datasets/trl-lab/SQaLe-text-to-SQL-dataset.spider-text-to-sql
Spider Text-to-SQL with LLM-Judge Labels
This dataset extends Spider 1.0 with SQL predictions from gpt-5.4-mini and two correctness labels per example: a hybrid ground truth label and an LLM judge label from gpt-5.4.
Files
File
Description
spider_dataset.parquet
Full dataset with predictions and labels
scripts/
Reproduction scripts (see below)
Dataset statistics
Source: Spider 1.0 training split (train_spider.json)
Databases: the… See the full description on the dataset page: https://huggingface.co/datasets/Glide-py/spider-text-to-sql.text-to-sql-shop
Text-to-SQL on a seeded store schema, with checkpoints
A question about an online store's database in, one PostgreSQL query out, graded by
a program: run the query, compare the result set to the gold query's result. The
schema (8 tables, seeded, schema.sql + seed.sql), the verifier, the trainer and
the benchmark runner are the
recipes/04-train/text-to-sql
recipe in the open-source whileai SDK.
Splits
config
rows
what
train
1764
tasks: question, gold_sql… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/text-to-sql-shop.text-to-sql-eval-predictions
What the text-to-SQL models actually generated
Every prediction behind the numbers in
qwen3-8b-text2sql-qlora: the 453 test
questions of the enterprise text-to-SQL benchmark,
each answered by four configurations of the same model, each answer executed against the reference
PostgreSQL database and scored by comparing result sets. 1,812 rows.
I published this because the headline table (10.82 % → 50.99 % → 52.10 %) is the least interesting part of
that project. The interesting… See the full description on the dataset page: https://huggingface.co/datasets/hari-krishna-ai/text-to-sql-eval-predictions.text-to-sql-phrasing-robustness
Does sloppy phrasing break text-to-SQL?
The enterprise text-to-SQL benchmark
lists its own biggest caveat: every question is template-generated, so real user phrasing is untested.
This is the test. 35 test questions (one per template), each sent to the deployed
pipeline four ways: as written, with a typo, in business shorthand, and stripped to a terse fragment.
24 questions and 85 answers survive the filter described under Setup; every answer was
executed against the database.… See the full description on the dataset page: https://huggingface.co/datasets/hari-krishna-ai/text-to-sql-phrasing-robustness.spider-text-to-sqltext_to_sql_ko
Korean Text to MySQL Dataset
Dataset Summary
Korean Text to MySQL is a dataset comprising approximately 3,300 samples generated using OpenAI's gpt-4o model. This dataset is designed to train models that convert natural language questions in Korean into MySQL queries. The data generation process was inspired by the Self-Instruct method and followed the steps outlined below.
Data Generation Process
1. Creation of SEED Dataset
Approximately 100 SEED samples were… See the full description on the dataset page: https://huggingface.co/datasets/won75/text_to_sql_ko.MycoBase-Large-Scale-Text-to-SQL
MycoBase: A Biologically Literate Text-to-SQL Dataset
MycoBase is a synthetic but biologically accurate dataset designed for stress-testing Text-to-SQL systems. It represents a research information system for the study of fungi, covering everything from taxonomy and genomics to morphology and cultivation.
Dataset Highlights
Schema Complexity: 2,016 tables with over 9,000 foreign key relationships.
Data Volume: 320,270 rows of realistic mycology data.
Realistic Names:… See the full description on the dataset page: https://huggingface.co/datasets/FatimahEmadEldin/MycoBase-Large-Scale-Text-to-SQL.