text2sql
There are 16 repositories under text2sql topic.
- Language:Java 14419
- sqlchatLanguage:TypeScript 4177
- ossinsight
pingcap / ossinsight
Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 7 billion with natural language (powered by OpenAI). Follow us on Twitter: https://twitter.com/ossinsight
Language:TypeScript 1709 eosphoros-ai / Awesome-Text2SQL
Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more.
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL
Language:Python 1247guotong1988 / NL2SQL-RULE
Content Enhanced BERT-based Text-to-SQL Generation https://arxiv.org/abs/1910.07179
Language:Python 188awslabs / gap-text2sql
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
Language:Python 100- Language:Jupyter Notebook 95
aws-samples / generative-bi-using-rag
A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG
Language:Python 77sz128 / Natural-language-understanding-papers
NLU: domain-intent-slot; text2SQL
- Language:Python 71
huybery / r2sql
:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)
Language:Python 61cami-la / mentoria_desmitificando_SQL_NoSQL_com_ChatGPT_Santander
Repositório referente a mentoria Desmestificando Banco de Dados SQL e NoSQL com ChatGT. Mentoria para os alunos participantes dos Bootcamps oferecido pela DIO em parceria com o Santander.
Language:Java 40chatc / TriageSQL
The dataset and source code for our paper: "Did You Ask a Good Question? A Cross-Domain Question IntentionClassification Benchmark for Text-to-SQL"
Language:Python 33This project uses the open-source model Mixtral 8x7B Instruct, deployed in Amazon SageMaker or invoked via API on Amazon Bedrock, to enable users to chat with their database using natural language, without writing any code or SQL query.
Language:Jupyter Notebook 15Table2answer: Read the database and answer without SQL https://arxiv.org/abs/1902.04260
Language:Python 15Using Database Rule for Weak Supervised Text-to-SQL Generation https://arxiv.org/abs/1907.00620
Language:Python 12ibm-ecosystem-engineering / QueryCraft
The easiest and most comprehensive framework for building enterprise-grade NL2SQL solutions at scale.
Language:Python 10weet-ai / text2sql-workshop
A basic Text2SQL App, powered by Langchain and OpenAI.
Language:Jupyter Notebook 7raffle-interns / SyntaxSQLNet
Python 3 reimplementation of SyntaxSQLNet, including several improvements
Language:Python 5hrshtv / CTreeOT
[ICML 2023] Official code for our paper: 'Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models'
Language:Python 4TristanLecourtois / NL2SQL
Text2SQL project comparing different LLM models
Language:Jupyter Notebook 4- Language:Go 3
emdemor / chatGPT-exemplos
Nesse repositório, eu sumarizo os casos de uso de chatGPT e LangChain que tenho estudado
Language:Jupyter Notebook 1brettdidonato / BSD_Evals
LLM evaluation framework
Language:Jupyter Notebook 0klima7 / Pol-Spider
Polish translation of spider dataset.
Language:Python 0Konex25 / ChatDB
Project proposal for solving the "Talk to your data" task at hackathon "HackYeah 2023"
Language:JavaScript 0- Language:Python
swastikmaiti / Fine-tuning-BART
Fine Tuning is a cost-efficient way of preparing a model for specialized tasks. Fine-tuning reduces required training time as well as training datasets. We have open-source pre-trained models. Hence, we do not need to perform full training every time we create a model.
Language:Jupyter Notebook
