datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sql-create-context
Overview
This dataset builds from WikiSQL and Spider.
There are 78,577 examples of natural language queries, SQL CREATE TABLE statements, and SQL Query answering the question using the CREATE statement as context. This dataset was built with text-to-sql LLMs in mind, intending to prevent hallucination of column and table names often seen when trained on text-to-sql datasets. The CREATE TABLE statement can often be copy and pasted from different DBMS and provides table names, column… See the full description on the dataset page: https://huggingface.co/datasets/b-mc2/sql-create-context.bird-critic-1.0-sqlite
📢 Update 2026-03-23
We release BIRD-Critic-SQLite, a dataset containing 500 high-quality user issues focused on real-world SQLite database applications. Along with the dataset, we also release three RL-trained models: BIRD-Talon-14B, BIRD-Talon-7B, and BIRD-Zeno-7B. The schema file is included in the code repository https://github.com/bird-bench/BIRD-CRITIC-1/blob/main/baseline/data/sqlite_schema.jsonl
BIRD-CRITIC-1.0-SQLite
BIRD-Critic is the first SQL debugging… See the full description on the dataset page: https://huggingface.co/datasets/birdsql/bird-critic-1.0-sqlite.bird_sql_dev_20251106
BIRD-SQL Dev
🆕 Update 2025-11-06
We would like to express our sincere gratitude to the community for their continuous support and constructive feedback on the BIRD-SQL Dev dataset. Over the past year, we have received valuable suggestions through GitHub discussions, emails, and user reports. Based on these insights, we organized a quality review program led by a team of five PhD researchers in Data Science and AI, supported by a globally distributed group of industry… See the full description on the dataset page: https://huggingface.co/datasets/birdsql/bird_sql_dev_20251106.livesqlbench-base-lite-sqlite
🚀 LiveSQLBench-Base-Lite
A dynamic, contamination‑free benchmark for evaluating LLMs on complex, real‑world text‑to‑SQL tasks.
🌐 LiveSQLBench Website • 🌐 BIRD-INTERACT Project Page • 📄 Paper • 💻 LiveSQLBench GitHub • 💻 BIRD-INTERACT GitHub
Maintained by the 🦜 BIRD Team @ HKU & ☁️ Google Cloud
📊 LiveSQLBench Overview
LiveSQLBench (BIRD-SQL Pro v0.5) is a contamination-free, continuously evolving benchmark designed to evaluate LLMs on complex, real-world… See the full description on the dataset page: https://huggingface.co/datasets/birdsql/livesqlbench-base-lite-sqlite.text-to-sql-shop
Text-to-SQL on a seeded store schema, with checkpoints
Recipe: recipes/04-train/text-to-sql · Collection: Analyst
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
|… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/text-to-sql-shop.SQL-API-Bench
Dataset Card for Dataset Name
This dataset contains QA that requires DB and API access at the same time. It is composed of two new benchmarks consisting of questions whose answers require a
combination of database and API calls, both of
which are augmentations of the popular Spider
dataset and benchmark.
Benchmark I replaces a fraction of the real Spider database tables with
equivalents that are executed via APIs. This allows us to directly test the mechanism by which
database and… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/SQL-API-Bench.six-gym-sqlite
📢 Update 2026-03-23
We release BIRD-Critic-SQLite, a dataset containing 500 high-quality user issues focused on real-world SQLite database applications. This dataset is the train split of BIRD-Critic-SQLite, comprising 5,000 data instances for model training and development. Along with the dataset, we also release three RL-trained models: BIRD-Talon-14B, BIRD-Talon-7B, and BIRD-Zeno-7B.
📋 Dataset Structure
Below is a description of the dataset fields and additional… See the full description on the dataset page: https://huggingface.co/datasets/birdsql/six-gym-sqlite.Text-to-sql-v1verified-sql-rewards
Verified SQL Rewards
A text-to-SQL corpus where every reward carries a machine-checkable proof
that it is correct.
Questions, all independently verified
109,306
Databases
1,400 across 7 schema families
Tables / data rows
4,400 / ~19.6 million
Unique (question, answer) pairs
102,764
Candidates refused and published
12,150
Verification pass rate
90.00%
Trivial baseline (always answer 0)
1.83%
Each item is a natural-language question, a gold SQL query… See the full description on the dataset page: https://huggingface.co/datasets/rasinmuhammed/verified-sql-rewards.BIRD-SQL-TRAINenterprise-text-to-sql-benchmark
Enterprise Text-to-SQL Benchmark
3,087 natural-language questions paired with executable PostgreSQL, over a
12-table enterprise schema (sales, catalogue, logistics, HR).
Built to answer one question honestly: does fine-tuning actually improve
text-to-SQL? On this benchmark, a QLoRA fine-tune of Qwen3-8B took strict
execution accuracy from 43.71 % to 68.43 %, and 70.86 % with a
self-correction loop — and the benchmark is designed so that number cannot be
inflated by leakage or by… See the full description on the dataset page: https://huggingface.co/datasets/hari-krishna-ai/enterprise-text-to-sql-benchmark.Persian-Business-Text-to-SQL-Gold-1K
Persian Business Text-to-SQL Gold-1K
1,000 Persian-native, execution-verified business Text-to-SQL examples for fine-tuning and benchmarking.
مجموعهای ۱۰۰۰ نمونهای برای تبدیل درخواستهای فارسی کسبوکار به SQL، همراه با دیتابیسهای SQLite اجرایی، schema کامل، متادیتای سختی/مهارت و ارزیابی مبتنی بر Execution Accuracy.
Motivation
BIRD emphasizes database-grounded Text-to-SQL and execution accuracy; Spider 2.0 pushes toward realistic enterprise database workflows.… See the full description on the dataset page: https://huggingface.co/datasets/jumplander/Persian-Business-Text-to-SQL-Gold-1K.bird-sql-mini-devav_sql_preprocessed_data
Dataset Card for Preprocessed Text-to-SQL Benchmarks
This repository contains preprocessed data for several text-to-SQL benchmarks, as presented in the paper AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views.
The official code for the AV-SQL framework can be found on GitHub: pminhtam/AV-SQL.
Dataset Summary
This repository contains preprocessed data for several text-to-SQL benchmarks:
BIRD
KaggleDBQA
Spider
sciencebenchmark
BEAVER
Spider2-Lite… See the full description on the dataset page: https://huggingface.co/datasets/griffith-bigdata/av_sql_preprocessed_data.bird-sqlite-sft-train
BIRD SQLite Text-to-SQL SFT Dataset
Supervised fine-tuning data for a SQLite-dialect text-to-SQL specialist model,
built from the BIRD benchmark train split.
Contents
7,483 train + 408 val examples spanning 69 distinct database schemas
(movie_platform, chicago_crime, hockey, mondial_geo, works_cycles, and 64
others), split by a stratified per-database 95/5 hold-out (sft_sqlite_ train.jsonl / sft_sqlite_val.jsonl) with zero exact overlap between them.
Format:… See the full description on the dataset page: https://huggingface.co/datasets/hiimivantang/bird-sqlite-sft-train.CSpider_and_DUSQL_sql_create_context此数据集原始数据集是合并CSpider和DUSQL。根据b-mc2/sql-create-context所创建。
sql-create-context-copy
Fork of b-mc2/sql-create-context
Overview
This dataset builds from WikiSQL and Spider.
There are 78,577 examples of natural language queries, SQL CREATE TABLE statements, and SQL Query answering the question using the CREATE statement as context. This dataset was built with text-to-sql LLMs in mind, intending to prevent hallucination of column and table names often seen when trained on text-to-sql datasets. The CREATE TABLE statement can often be copy and pasted from… See the full description on the dataset page: https://huggingface.co/datasets/philschmid/sql-create-context-copy.sql-optimizer
Dataset Card for Dataset Name
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/k19862217/sql-optimizer.know_sqlplease use the val ign file for training, its much cleaner. thanks :)
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.Effi-SQL
Effi-SQL
Update 2026-06-12
We release Effi-SQL, a dataset suite for SQL efficiency optimization.
This collection includes:
Effi-SQL Benchmark: a benchmark for evaluating SQL efficiency optimization methods.
Diff-SQL Training Dataset: training data used by Diff-SQL, including data for the Patch Generator and Constraint Aligner.
Dataset Fields
Effi-SQL Benchmark
id: A unique identifier for each benchmark instance.
db: The database… See the full description on the dataset page: https://huggingface.co/datasets/birdsql/Effi-SQL.sql-text-collection
SQL Text Collection
This is a collection of publicly available text-to-SQL datasets.
Dataset Structure
Each row contains the columns:
context: The schema for the database (e.g., CREATE TABLE statements).
query: A natural language query or action to perform, expressed in English.
source: The original dataset from which the row was sourced.
dialect: One or more SQL dialects identified based on dialect-specific keywords found in the context and query.
If there are multiple… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/sql-text-collection.sql-injection
SQL注入推理能力微调数据集
概述
本数据集旨在帮助研究人员和工程师通过特定案例来微调模型在SQL注入（SQLi）检测与预防方面的能力。SQL注入是一种代码注入技术，攻击者通过将恶意的SQL查询或语句插入应用程序的输入字段中，以操纵数据库执行非授权的操作。
数据集用途
研究用途：为安全领域的研究人员提供实际案例，以便于探索和开发新的防御策略。
模型训练：为机器学习模型提供训练素材，以提高其识别和防范SQL注入攻击的能力。
教育目的：作为教育资源，帮助学生和新手了解SQL注入的风险及其防护措施。
获取更多数据
如需获取更多相关数据或希望参与贡献，请访问我们的GitHub仓库：
AAuZZ/SQLiDataset
许可证
本项目使用Apache 2.0许可证。有关详细信息，请参阅LICENSE文件。
Dataset for Fine-tuning Reasoning Ability in SQL Injection
Overview… See the full description on the dataset page: https://huggingface.co/datasets/Kaveny/sql-injection.spider-text-2-sqlmirror-sql
MIRROR-SQL
Provenance-Controlled Database Environments for Text-to-SQL Agents.
13 PostgreSQL environments · 176 tables · 2762 columns · 390 annotated question/SQL pairs.
MIRROR-SQL takes the opposite approach to contamination from every other text-to-SQL corpus.
Spider and BIRD sample public databases. BEAVER uses real private warehouses that cannot be
redistributed. LiveSQLBench out-runs leakage temporally by rebuilding from changing sources.
MIRROR-SQL instead purpose-builds… See the full description on the dataset page: https://huggingface.co/datasets/1digitaldesign/mirror-sql.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.SQLFlow
Text2SQL-Flow Dataset Repository
This repository contains the SQLFlow dataset.
The SQLFlow dataset is a large-scale, high-quality collection of semantically valid and structurally diverse Text-to-SQL examples, generated using a comprehensive SQL-aware data augmentation framework.
For more details, please visit the GitHub repository:🔗 https://github.com/TechNomad-ds/Text2SQL-Flow
sql-query-engine-synthetic
SQL Query Engine — Synthetic Benchmark
A gold-standard NL-to-SQL benchmark containing 75 natural language questions across 3 PostgreSQL databases (e-commerce, university, hospital), each with verified gold SQL queries and expected results. Designed to evaluate text-to-SQL systems with a focus on measuring the impact of iterative self-healing (query repair) loops.
Paper
SQL Query Engine: A Self-Healing LLM Pipeline for Natural Language to PostgreSQL Translation
Muhammad… See the full description on the dataset page: https://huggingface.co/datasets/codeadeel/sql-query-engine-synthetic.sql-create-context-id
Overview
This dataset is a fork from sql-create-context
This dataset builds from WikiSQL and Spider.
There are 78,577 examples of natural language queries, SQL CREATE TABLE statements, and SQL Query answering the question using the CREATE statement as context. This dataset was built with text-to-sql LLMs in mind, intending to prevent hallucination of column and table names often seen when trained on text-to-sql datasets. The CREATE TABLE statement can often be copy and pasted from… See the full description on the dataset page: https://huggingface.co/datasets/detakarang/sql-create-context-id.Text-to-sql-v1