datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Text-to-sql-v1text-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.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.spanish_text_to_unitenterprise-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.text-to-ocl-from-ecore
Introduction
This is a small size dataset containing 52 meta-models (EMF files and PlantUML descriptions), 369 OCL constraints and 369 constraint specification in natural language.
The meta-models and OCL constraints are collected from open source github projects and are (syntactically) processable by Eclipse.
The constraint specifications of OCL constraints are generated via GPT-4-Turbo.
The meta-models can be found in models\
Usage
Generation of OCL constraints based on… See the full description on the dataset page: https://huggingface.co/datasets/fpan/text-to-ocl-from-ecore.text-to-xmi-from-ecoreThis is a small test set for XMI instance model generation task.
It containing 26 pairs of meta-models (Ecore), specifications (natural language) and instance models (XMI).
In each pair, the meta-model and instance model share the same name. To proper open the instance model in Eclipse EMF, the instance model and meta-model should be placed in the same folder.
The meta-models are selected from https://huggingface.co/datasets/fpan/text-to-ocl-from-ecore.
The specifications are generated via… See the full description on the dataset page: https://huggingface.co/datasets/fpan/text-to-xmi-from-ecore.trending-text-to-image
CivitAI Improved Prompts Dataset
This dataset contains trending AI-generated images from CivitAI with Flux-improved prompts for better generation results.
Dataset Format (JSONL)
Each line contains a JSON object with:
id: Original image ID from CivitAI
improved_prompt: Flux-enhanced version of the prompt
category: Automatically determined theme category
All original CivitAI metadata including:
Original prompt and negative prompt
Model information
Image URL and… See the full description on the dataset page: https://huggingface.co/datasets/k-mktr/trending-text-to-image.adapt-pre-trained-VL-models-to-text-data-WikipediaThe Wikipedia train data used to train BERT-base baselines and adapt vision-and-language models to text-only tasks in the paper "How to Adapt Pre-trained Vision-and-Language Models to a Text-only Input?".
The data has been created from the "20200501.en" revision of the wikipedia dataset on Huggingface.
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.Rotowire-Text-to-Table
RotoWire Corrected Test Set
Dataset Description
This is the corrected test set for the RotoWire dataset, released as part of the Map&Make: Schema Guided Text to Table Generation paper (ACL 2025). The original RotoWire dataset contained hallucination errors where the ground truth tables included incorrect or fabricated statistics. This corrected version provides a cleaner benchmark for text-to-table generation tasks.
Motivation: Why We Need This Corrected… See the full description on the dataset page: https://huggingface.co/datasets/McH04/Rotowire-Text-to-Table.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.text-to-svg
Text-to-SVG Dataset
Overview
This dataset is curated to support training and evaluating large language models (LLMs) for text-to-SVG generation tasks.It combines multiple high-quality sources to provide a diverse and comprehensive collection of SVG code examples paired with textual prompts and structured instructions.The focus is on enabling models to generate standards-compliant SVG graphics from descriptive language.
Dataset Composition
1️⃣ Visual… See the full description on the dataset page: https://huggingface.co/datasets/wexhi/text-to-svg.Text-To-Memory-Synthetictext-to-command-geminiText-to-TsqlText-to-sql-v1text-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-cypherdataframer_text_to_sqltext-to-jsonadapt-pre-trained-VL-models-to-text-data-Wikipedia-finetuneThe Wikipedia finetune data used to train visual features for the adaption of vision-and-language models to text-only tasks in the paper "How to Adapt Pre-trained Vision-and-Language Models to a Text-only Input?".
The data has been created from the "20200501.en" revision of the wikipedia dataset on Huggingface.
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-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.adapt-pre-trained-VL-models-to-text-data-LXMERTThe LXMERT text train data used to train BERT-base baselines and adapt vision-and-language models to text-only tasks in the paper "How to Adapt Pre-trained Vision-and-Language Models to a Text-only Input?".
The data has been created from the data made available by the LXMERT repo.
text_to_dbt
text_to_dbt
A synthetic instruction-tuning dataset for fine-tuning language models on natural language → dbt DAG generation.
Each example pairs a business question + SQL schema with a complete, multi-file dbt project structure validated by dbt parse.
Dataset summary
Split
Rows
train
900
test
100
Total
1 000
Fields per row: messages (chat format, compatible with Qwen3 / Mistral / OpenAI chat templates).
What is a dbt DAG?
A dbt (data build… See the full description on the dataset page: https://huggingface.co/datasets/tdelard/text_to_dbt.text-to-opensearch-dsl-multi-turn-2text-to-chart-spec-dataset
Text-to-Chart-Spec Dataset
96% Win Rate on Adaption AutoScientist Challenge
Overview
This dataset was created for the Adaption AutoScientist Challenge in the Data Visualization and Chart Interpretation category.
Dataset Statistics
Metric
Value
Total Examples
18,003
Format
JSONL (prompt/completion)
Task
Text to Chart Specification
Win Rate
96%
Output Format
The model outputs chart specifications in a structured… See the full description on the dataset page: https://huggingface.co/datasets/pandeyankit84/text-to-chart-spec-dataset.python-text-to-codetext_to_schema.org_json-ld