nsql-6B
Maintainer: NumbersStation
50
✅
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
NSQL is a family of autoregressive open-source large foundation models (FMs) designed specifically for SQL generation tasks. The NSQL-6B checkpoint included in this repository is based on CodeGen-Multi 6B from Salesforce and further pre-trained on a dataset of general SQL queries and then fine-tuned on a dataset composed of text-to-SQL pairs.
Similar models in this family include the [object Object] and [object Object] which are based on Meta's Llama-2 and fine-tuned for SQL generation, as well as the more broadly capable [object Object] model from ChatDB.
Model inputs and outputs
NSQL-6B is a text-to-text model designed for SQL generation tasks. Given a natural language prompt and database schema, the model can generate valid SQL queries to answer the given question.
Inputs
- Natural language prompts or questions related to a database schema
- Database schema definition in the form of SQL
CREATE TABLEstatements
Outputs
- SQL queries that answer the given prompt or question, typically in the form of
SELECTstatements
Capabilities
The NSQL-6B model excels at translating natural language questions into SQL queries for a given database schema. It can handle a wide range of SQL constructs, including SELECT, WHERE, JOIN, ORDER BY, GROUP BY, and more. The model has shown strong performance on text-to-SQL benchmarks like Spider and GeoQuery.
What can I use it for?
NSQL-6B can be a powerful tool for automating the process of converting natural language requests into SQL queries. This can be useful in a variety of applications, such as:
- Building conversational interfaces for databases, allowing users to query data using natural language
- Generating SQL code to power business intelligence and reporting tools
- Assisting developers in quickly prototyping and iterating on database-backed applications
- Enhancing productivity for data analysts and scientists who need to frequently interact with databases
Things to try
One interesting aspect of the NSQL model family is the ability to fine-tune the models for specific database systems and use cases. For example, the [object Object] model is fine-tuned on DuckDB-specific text-to-SQL pairs, allowing it to generate queries that leverage DuckDB's unique features and extensions.
Developers and data professionals could experiment with fine-tuning the NSQL-6B model on their own dataset of SQL queries and database schemas to create a highly customized SQL generation assistant tailored to their specific needs.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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