datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
synthetic_text_to_sql
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synthetic_text_to_sql
gretelai/synthetic_text_to_sql is a rich dataset of high quality synthetic Text-to-SQL samples,
designed and generated using Gretel Navigator, and released under Apache 2.0.
Please see our release blogpost for more details.
The dataset includes:
105,851 records partitioned into 100,000 train and 5,851 test records
~23M total tokens, including ~12M SQL tokens
Coverage across 100 distinct… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/synthetic_text_to_sql.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.gretel-synthetic-text-to-sql
Fork of gretelai/synthetic_text_to_sql
The gretelai/synthetic_text_to_sql dataset is a large, Apache 2.0 licensed, synthetic Text-to-SQL dataset consisting of 105,851 high-quality records across 100 diverse domains, designed for training language models. It includes comprehensive SQL tasks with varying complexities, database contexts, natural language explanations, and contextual tags, outperforming existing datasets in SQL correctness and standards compliance.
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-v1Persian-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.text-to-sql-spider-dataset
Text-to-SQL Dataset
A curated dataset for training text-to-SQL models. This dataset contains natural language questions paired with corresponding SQL queries, formatted for instruction fine-tuning.
📊 Dataset Summary
Total Samples: 20000
Format: Chat template (system/user/assistant messages)
Task: Text-to-SQL generation
Language: English
License: apache-2.0
📁 Dataset Structure
Data Format
Each example contains a conversation with three roles:… See the full description on the dataset page: https://huggingface.co/datasets/chrisjcc/text-to-sql-spider-dataset.enterprise-text-to-sql-benchmark
Enterprise Text-to-SQL Benchmark
3,045 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 10.82 % to 50.99 % — and the benchmark is designed
so that number cannot be inflated by leakage or by string-matching.
split
rows… See the full description on the dataset page: https://huggingface.co/datasets/hari-krishna-ai/enterprise-text-to-sql-benchmark.enterprise-text-to-sql-verified
Verified Multi-Dialect Enterprise Text-to-SQL Dataset
This dataset contains 100% deterministically verified Text-to-SQL instruction pairs across multiple cloud warehouse dialects (DuckDB, PostgreSQL, Snowflake, BigQuery).
Features
Deterministic Execution: Every query executed and verified in DuckDB memory before ingestion.
Multi-Dialect Translation: Native PostgreSQL, Snowflake, and BigQuery transpiled variants included.
ShareGPT Structured: Formatted for direct… See the full description on the dataset page: https://huggingface.co/datasets/Zeknichov/enterprise-text-to-sql-verified.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.enterprise-sql-text-to-db-sft-dpo-2026
💎 Enterprise SQL, Text-to-DB & Schema-Aware Query Architect SFT/DPO Dataset (2026)
High-precision instruction tuning and preference optimization dataset with step-by-step Chain-of-Thought (<thought>) reasoning chains for fine-tuning LLMs (Llama-3.3, Qwen-2.5-Coder, DeepSeek-R1-Distill, Mistral, Phi-4) into Senior Enterprise Database Architects.
📊 Dataset Overview
Format: OpenAI ChatML & ShareGPT format with <thought> reasoning tokens.
Dialect Coverage (5… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/enterprise-sql-text-to-db-sft-dpo-2026.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-v1text-to-sql-mix-v1
Text-to-SQL Training Mix v1
A curated, deduplicated and quality-filtered mix of six high-quality
text-to-SQL datasets from HuggingFace, designed for fine-tuning code LLMs
(Qwen 2.5 Coder, DeepSeek Coder, Llama-3, etc.) on SQL generation.
This dataset powers the SQL Generator in the SQL Agent LLMOps project.
Schema
Field
Type
Description
id
string
Stable hash-based identifier
instruction
string
Natural language question / instruction
schema_context
string… See the full description on the dataset page: https://huggingface.co/datasets/DanielRegaladoCardoso/text-to-sql-mix-v1.synthetic_chat_text_to_sqltext-to-sql-dataset
English Text‑to‑SQL with Optional Schema
This dataset maps English user questions to SQL queries, with or without a compact database schema provided. The schema, when present, is a minimal representation of the database structure: a comma‑separated list of table names followed by their column names in parentheses. No data types are included.
Dataset Structure
Column
Type
Description
text
string
The user's request in English.
schema
string (optional)… See the full description on the dataset page: https://huggingface.co/datasets/sirunchained/text-to-sql-dataset.text-to-sql-mix-v2
🔗 Part of the SQL Agent LLMOps project
This dataset is one of three purpose-built training mixes for the
SQL Agent LLMOps project — an end-to-end pipeline that
converts natural-language questions into SQL, executes the query on user
data, and renders a storytelling-grade visualization.
Dataset
Model trained
Role
🤗 DanielRegaladoCardoso/text-to-sql-mix-v2
Qwen 2.5 Coder 7B
NL question → SQL
🤗 DanielRegaladoCardoso/chart-reasoning-mix-v1Phi-3 Mini 3.8B
(question +… See the full description on the dataset page: https://huggingface.co/datasets/DanielRegaladoCardoso/text-to-sql-mix-v2.pt-br-agentic-text-to-sql-distilled-trajectories
PT-BR Agentic Text-to-SQL Distilled Trajectories
This dataset contains message-only distilled trajectories for training tool-using Text-to-SQL agents in Brazilian Portuguese. The trajectories were selected from LLM-judged correct conversations and preserve the agent protocol used in the released code.
Code and reproducibility repository:
https://github.com/Boakpe/distilled-slms-for-text-to-sql-pt-br
Related collection:… See the full description on the dataset page: https://huggingface.co/datasets/Boakpe/pt-br-agentic-text-to-sql-distilled-trajectories.synthetic_text_to_sql_en_es
Dataset basado en la versión de GretelAI - SyntheticSQL
synthetic_text_to_sql_en_es
Se trata de una expansión mediante la traducción al español de la columna 'sql_prompt'.
Se ha añadido una columna extra 'sql_prompt_es' que contiene el prompt original de inglés traducido al español.
Para obtener estas traducciones, se utilizó few-shot prompting + CoT mediante el modelo Qwen/Qwen2.5-32B-Instruct-AWQ
Actualización 6/27/25
En la versión pasada se encontraron… See the full description on the dataset page: https://huggingface.co/datasets/TafcoMetawireless/synthetic_text_to_sql_en_es.text-to-sql-struct-distillation-sft
结构化 Text-to-SQL 蒸馏 SFT（本地通用导出）
这是本项目完整的结构化 Text-to-SQL SFT 导出，共 6,246 条 messages 格式 JSONL 样本；其中正式 Qwen3-8B 实验实际使用的是本仓库中明确标注的 5,160 条训练 split。
文件与划分
qwen_sft_messages.jsonl：全量 SFT，6,246 条。
splits/dbdev4_train_5160.jsonl：正式 Qwen3-8B LoRA 训练集，5,160 条。它是全量教师样本按数据库划分后的子集，对应训练机中的 qwen_sft_messages_train_dbdev4.jsonl。
splits/dbdev4_execution_dev_prompts_400.jsonl：训练期 database-disjoint execution-dev 的 400 条提示词，只含 system/user messages，不含 gold SQL。… See the full description on the dataset page: https://huggingface.co/datasets/craboy4/text-to-sql-struct-distillation-sft.synthetic_text_to_sqlreasoning-sft-synthetic_text_to_sql-128K
synthetic_text_to_sql (converted)
Converted version of gretelai/synthetic_text_to_sql, reformatted to 100,000 rows for reasoning SFT training.
Format
Each row has three columns:
input — list of dicts [{"role": "system", "content": "..."}, {"role": "user", "content": "..."}] (system prompt contains the database schema, user prompt contains the natural language question)
response — response string with <think> reasoning block (SQL explanation) followed by the SQL query… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-synthetic_text_to_sql-128K.synthetic_text_to_sql_reasoning
Synthetic Text-to-SQL with Reasoning Traces
This dataset is an enhanced version of gretelai/synthetic_text_to_sql with synthetic reasoning traces added using Nemo Data Designer and openai/gpt-oss-120b for generation.
Dataset Description
gretelai/synthetic_text_to_sql is a rich dataset of high quality synthetic Text-to-SQL samples, designed and generated using Gretel Navigator, and released under Apache 2.0.
The original dataset includes:
105,851 records partitioned into… See the full description on the dataset page: https://huggingface.co/datasets/meowterspace45/synthetic_text_to_sql_reasoning.synthetic-text-to-sql-tr
Cognipeer/synthetic-text-to-sql-tr
Overview
Cognipeer/synthetic-text-to-sql-tr is a Turkish translation of the gretelai/synthetic_text_to_sql dataset. gretelai/synthetic_text_to_sql is a rich dataset of high quality synthetic Text-to-SQL samples, designed and generated using Gretel Navigator, and released under Apache 2.0.
Dataset Features: The dataset includes 12 main feature:
id (int32)
domain (string)
domain_description (string)
sql_complexity (string)… See the full description on the dataset page: https://huggingface.co/datasets/Cognipeer/synthetic-text-to-sql-tr.synthetic-text-to-sql-tangle
Synthetic Text-to-SQL — Tangle SFT demo subset
A small, fixed subset of gretelai/synthetic_text_to_sql
(Apache-2.0), prepared for an end-to-end supervised fine-tuning showcase running as a
Tangle pipeline.
train.jsonl — first 5,000 rows of the source train split.
eval.jsonl — first 500 rows of the source test split.
train.tiny.jsonl / eval.tiny.jsonl — 16 / 8 rows, for a fast CPU wiring dry-run.
Each row keeps five fields from the source: id, domain, sql_prompt (the… See the full description on the dataset page: https://huggingface.co/datasets/ml-infra-toloka/synthetic-text-to-sql-tangle.synthetic_text_to_sql_d14
This dataset is subset of "gretelai/synthetic_text_to_sql"
Data Cleaning
The original dataset get filtered based on the following criteria:
(sql_context + sql) Validate against the SQLite database.
Tables must have some records.
We must get some output after running the "sql" query.
Subset Creation
I picked 3 sql complexity and 14 domains to create a subset.
SQL_COMPLEXITY = ['basic SQL', 'aggregation','single join']
DOMAINS = [
"technology", "sports", "logistics"… See the full description on the dataset page: https://huggingface.co/datasets/djagatiya/synthetic_text_to_sql_d14.synthetic-complex-Text-to-SQL
Synthetic Complex Text-to-SQL
Synthetic Text-to-SQL using multiple joins, WHERE statements, window and aggregate functions on filtered SQL from bigcode/the-stack.
smolified-tiny-text-to-sql
🤏 smolified-tiny-text-to-sql
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model vardhan-yash/smolified-tiny-text-to-sql.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 4b9509ca)
Records: 320
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by vardhan-yash.
Generated via Smolify.ai.
smolified-tiny-text-to-sql
🤏 smolified-tiny-text-to-sql
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model Aishwarya0803/smolified-tiny-text-to-sql.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 648ad32f)
Records: 8960
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by Aishwarya0803.
Generated via Smolify.ai.
text-to-sql-struct-distillation-minidev
结构化 Text-to-SQL 蒸馏 Mini-Dev 派生 SFT
本仓库发布由 BIRD Mini-Dev 500 个样本构造的派生 SFT messages 数据，共 500 条。
文件与边界
minidev_sft_messages.jsonl：500 条 messages 格式的派生 SFT 样本。
不含 Mini-Dev SQLite 数据库、gold SQL、原始 schema 文件或上游数据库内容。
评测中使用 BIRD 作者提供的 SQLite 集合型 Execution Accuracy (EX) 定义；该评测代码与复现说明在 GitHub 工程中维护。
来源、署名与许可证
本数据为 BIRD Mini-Dev 的派生文本内容。上游仓库：https://github.com/bird-bench/mini_dev。上游 README 标明 CC BY-SA 4.0，因此本仓库按 CC BY-SA 4.0 发布。使用或再发布时请保留对 BIRD 与 Mini-Dev… See the full description on the dataset page: https://huggingface.co/datasets/craboy4/text-to-sql-struct-distillation-minidev.