datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
synthetic-text2sqlEmploying the MTEB evaluation framework's dataset version, utilize the code below for assessment:
import mteb
import logging
from sentence_transformers import SentenceTransformer
from mteb import MTEB
logger = logging.getLogger(__name__)
model_name = 'intfloat/e5-base-v2'
model = SentenceTransformer(model_name)
tasks = mteb.get_tasks(
tasks=[
"AppsRetrieval",
"CodeFeedbackMT",
"CodeFeedbackST",
"CodeTransOceanContest",
"CodeTransOceanDL"… See the full description on the dataset page: https://huggingface.co/datasets/CoIR-Retrieval/synthetic-text2sql.spider-text2sql
SPIDER Text-to-SQL — Easy Access Version
A clean, HuggingFace-native version of the SPIDER Text-to-SQL benchmark. The original SPIDER dataset requires manually downloading a ZIP file from the Spider website. This version makes it instantly accessible via load_dataset.
What's Included
Each row contains the question, gold SQL, the database identifier, and a pre-parsed compact schema string — everything needed to train or evaluate a Text-to-SQL model without any additional… See the full description on the dataset page: https://huggingface.co/datasets/SuperMax991/spider-text2sql.large-schema-text2sql-20k
Large-Schema Text-to-SQL (20K)
20,020 text-to-SQL examples whose median database schema has 95 tables.
Most text-to-SQL corpora hand the model a toy database. Spider averages about 5 tables per
database; BIRD is in the same range. Real analytics work does not look like that — it looks
like an ERP schema with 200 tables, 300 foreign keys, and eleven things called *_log, where
the hard part is not writing the JOIN but finding the two tables worth joining.
This dataset is that… See the full description on the dataset page: https://huggingface.co/datasets/VikramPal/large-schema-text2sql-20k.text2sql-dataset
Dataset
We built this dataset from several sources combining examples from:
Wikisql
Bird
Spider
Synthetic SQL samples
This dataset has been cleaned and filtered by:
Removing DDL/DML examples (INSERT, UPDATE, DELETE, etc.)
De-duplicating examples based on hashing semantics of SQL and queries
Filtering only SELECT-style analytical queries
synthetic-text2sql-qrels
Dataset Card for "synthetic-text2sql-qrels"
More Information needed
synthetic-text2sql-dataset
Dataset Card for "synthetic-text2sql-dataset"
Dataset Summary
The synthetic-text2sql-dataset is a large-scale, structured dataset containing 100,000 training and 5,851 test examples designed to support research and development in SQL semantic parsing, text-to-SQL generation, and chain-of-thought (CoT) reasoning.
It was derived from an original DataFrame and converted into Hugging Face's datasets.Dataset format. Three new fields were added:
question: alias for the… See the full description on the dataset page: https://huggingface.co/datasets/eagle0504/synthetic-text2sql-dataset.synthetic-text2sql-queries-corpusEmploying the CoIR evaluation framework's dataset version, utilize the code below for assessment:
import coir
from coir.data_loader import get_tasks
from coir.evaluation import COIR
from coir.models import YourCustomDEModel
model_name = "intfloat/e5-base-v2"
# Load the model
model = YourCustomDEModel(model_name=model_name)
# Get tasks
#all task ["codetrans-dl","stackoverflow-qa","apps","codefeedback-mt","codefeedback-st","codetrans-contest","synthetic-
# text2sql","cosqa","codesearchnet"… See the full description on the dataset page: https://huggingface.co/datasets/CoIR-Retrieval/synthetic-text2sql-queries-corpus.wikisql-text2sql
WikiSQL Text-to-SQL (execution-ready)
A cleaned, execution-ready repackaging of WikiSQL
for text-to-SQL fine-tuning and execution-accuracy evaluation. Each example pairs a
natural-language question with a gold SQL query over a single-table schema — and every split
ships a real SQLite database so predicted SQL can be run and compared by result set
(not string-matched).
Splits
Split
Examples
train
55,339
dev
8,263
test
15,519
Columns… See the full description on the dataset page: https://huggingface.co/datasets/mohamed-ahmed-58059/wikisql-text2sql.bird-text2sql-bench
Dataset Card for bird-text2sql-bench
bird-text2sql-bench 是 BIRD（BIg Bench for Large-Scale Database Grounded Text-to-SQL） 官方訓練集之 OpenAI Messages 格式版本，共 9,428 筆。相較於 Spider 1.0，BIRD 使用真實大型資料庫（70 個，涵蓋電商、運動、教育、醫療等 37+ 領域），並提供 evidence（數值提示）欄位，本資料集將 evidence 以 ### Hint 段落併入 user prompt，形成可直接餵入 SFT pipeline 之 system / user / assistant 三 role 對話。除原生之 messages 欄位外，另拆解出獨立之 system / user / assistant 字串欄位，可同時作為 SFT 語料與 benchmark evaluation pipeline 之直接輸入。
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/bird-text2sql-bench.200k-Text2SQLtext-2-sql-with-context
Dataset Card for "text-2-sql-with-context"
This dataset is prepared in Alpaca format introduced by Stanford to train LLMs. This dataset has been used in fine-tuning Chat Llama-2 7B. For more information, Please visit : Huggingface.
text2sql-spider
Dataset Card for "text2sql-spider-processed"
More Information needed
synthetic-text2sqlfor_text2sql_wikiSQL_korean_by_google_translator_apitext2sql-wikisql-spider
Dataset Card for "text2sql-wikisql-spider"
More Information needed
sft_text2sqlThis is the SFT training dataset for FINER-SQL on BIRD dataset. We use different LLMs from the LLM pool to generate diversed reasoning styles and diversed SQL styles.
The model pool includes: GPT-OSS-120b, Qwen-2.5-72B-Instruct, Deepseek-R1, GPT-5 (reasoning_effort=low)
Note that:
GPT-5 could be replaced by GPT-4o or GPT-4.1, because OpenAI doesn't return their true reasoning process so generating by GPT-5 was not necessary.
The schema filtering (top-30 columns) was applied before generating… See the full description on the dataset page: https://huggingface.co/datasets/griffith-bigdata/sft_text2sql.spider-text2sql-bench
Dataset Card for spider-text2sql-bench
spider-text2sql-bench 是 Spider 1.0 官方訓練集之 OpenAI Messages 格式版本，共 7,000 筆，將原始之 question / schema / sql 重新組裝為 system / user / assistant 三 role 之對話結構。除原生之 messages 欄位外，另拆解出獨立之 system / user / assistant 字串欄位，可作為 Text-to-SQL 模型之 SFT 訓練語料，亦可直接用於 benchmark evaluation pipeline（以 user 作為 prompt，比對模型輸出與 assistant 之標準答案 SQL）。
Dataset Details
Dataset Description
Spider 1.0 為 Yale LILY Group 於 EMNLP 2018 發表之大規模跨領域 Text-to-SQL… See the full description on the dataset page: https://huggingface.co/datasets/lianghsun/spider-text2sql-bench.Text2SQLsql-text2sql-datasettext2sql-canonical-v2Vin-Text2SQL-fewshottext2sqltext2sql-canonical-v3.1
text2sql-canonical-v3.1
Training data for a SQLite text-to-SQL model: 51,976 training rows and
a 527-row validation split. Each row holds a database schema rendered
as text, a natural-language question, an optional evidence hint, and
the reference SQL. The mix caps synthetic data at 40 percent and gives
real benchmark rows double weight.
Split
Rows
BIRD
Spider
SynSQL
train
51,976
33%
27%
40%
val
527
34%
27%
40%
Columns
db_id, question, gold_sql… See the full description on the dataset page: https://huggingface.co/datasets/mohamed-ahmed-58059/text2sql-canonical-v3.1.Text2SQL-solar-ProText2SQL_instruction_datasettext2sql_argilla
Dataset Card for text2sql_argilla
This dataset has been created with Argilla.
As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.
Dataset Summary
This dataset contains:
A dataset configuration file conforming to the Argilla dataset format named argilla.yaml. This configuration file will be used to configure the dataset when using the… See the full description on the dataset page: https://huggingface.co/datasets/Kamaljp/text2sql_argilla.text2sql-dataset-reasoningtext2Sql_v1text2Sql_v2text2sql_vi