text-2-sql
Code-Llama-2-13B-instruct-text2sql-GGUFArctic-Text2SQL-R1-7BArctic-Text2SQL-R1-7B-i1-GGUFArctic-Text2SQL-R1-7B-GGUFSEUNGYEOPOH_-_gemma-2-2B-Text_to_SQL-mv-ggufXeAI_-_LLaMa_3.2_3B_Instruct_Text2SQL_Legacy-ggufhuyhoangt2201_-_llama3.2-1b-text2SQL-finetuned-multitableJidouka2.1-ggufSiriusAI-Text2SQL-27b-agentic-v1-GGUF
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.text2sql-eval-results
Text2SQL Evaluation Toolkit — Pre-computed Results
Pre-computed inference and evaluation results produced by the
IBM/text2sql-eval-toolkit
across six text-to-SQL benchmarks.
These artefacts power the toolkit's evaluation dashboard and analysis scripts
without requiring you to re-run multi-hour inference pipelines.
Quick start
Install the toolkit and fetch all results (~3.8 GB):
pip install text2sql-eval-toolkit
text2sql-eval-toolkit results fetch
Fetch a single… See the full description on the dataset page: https://huggingface.co/datasets/text2sql-eval-toolkit/text2sql-eval-results.SQaLe-2-text-to-SQL-SchemasSQaLe: schemas and databases
Project page ·
Questions and SQL ·
Trained models ·
Python library ·
Citation
This dataset holds the 9,259 populated databases of SQaLe, a large semi-synthetic text-to-SQL dataset grounded in real-world database schemas, introduced in the paper SQaLe: a large realistic dataset to empower small specialised text-to-SQL models. Each row is one database: its DDL, extended from a real schema in SchemaPile, and the generated rows of its tables. The… See the full description on the dataset page: https://huggingface.co/datasets/trl-lab/SQaLe-2-text-to-SQL-Schemas.synthetic-text2sql-qrels
Dataset Card for "synthetic-text2sql-qrels"
More Information needed
SQaLe-2-text-to-SQL-QueriesSQaLe: questions and SQL
Project page ·
Schemas and databases ·
Trained models ·
Python library ·
Citation
SQaLe is a large semi-synthetic text-to-SQL dataset grounded in real-world database schemas, introduced in the paper SQaLe: a large realistic dataset to empower small specialised text-to-SQL models. It pairs 1,408,056 natural-language questions with 176,761 distinct SQL queries over 9,259 populated SQLite databases. The schemas come from SchemaPile, a collection of database… See the full description on the dataset page: https://huggingface.co/datasets/trl-lab/SQaLe-2-text-to-SQL-Queries.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