t5-base-text-to-sql Open-source Model - Freely Convert English Natural Language Queries into SQL Queries

T5 Base Text To Sql

Developed by suriya7

A fine-tuned version based on Google's T5-small model, specifically designed for translating English natural language queries into SQL SELECT statements.

Machine Translation

Transformers

Open Source License:MIT #English to SQL #Database query generation #T5 fine-tuning

Downloads 941

Release Time : 3/19/2024

Model Overview

This model can understand English queries and generate corresponding SQL SELECT statements, providing significant value for automating the conversion from natural language to SQL (especially SELECT operations).

Model Features

English to SQL translation

Accurately translates English natural language queries into SQL SELECT statements.

Fine-tuned on T5-small

Optimized for English-to-SQL SELECT translation performance by fine-tuning Google's T5-small model.

Multi-domain support

Trained on data from various domains, capable of handling diverse types of queries.

Model Capabilities

Natural language processing

Text-to-text conversion

SQL query generation

Use Cases

Database queries

Employee salary query

Converts the English query 'Show all employees with salaries over $50,000' into an SQL query.

Generates the corresponding SQL SELECT statement

Model statistics query

Converts the English query 'How many models are fine-tuned based on BERT?' into an SQL query.

Generates the corresponding SQL SELECT statement

Vehicle query

Converts the English query 'How many blue cars are there?' into an SQL query.

Generates the corresponding SQL SELECT statement

🚀 T5-SQL-Translator

T5-SQL-Translator is a fine - tuned model that specializes in translating English natural language queries into SQL SELECT queries, streamlining the process of database interaction.

🚀 Quick Start

To start using the T5 - SQL - Translator, you first need to install the Hugging Face Transformers library.

pip install transformers

✨ Features

Specialized in translating English natural language queries into SQL SELECT queries.
Automates the process of natural language to SQL translation, especially for SELECT operations.

📦 Installation

Install the Hugging Face Transformers library using the following command:

pip install transformers

💻 Usage Examples

Basic Usage

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("suriya7/t5-base-text-to-sql")
model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/t5-base-text-to-sql")

def translate_to_sql_select(english_query):
    input_text = "translate English to SQL: " + english_query
    input_ids = tokenizer.encode(input_text, return_tensors="pt", max_new_tokens=100, do_sample=False)
    outputs = model.generate(input_ids)
    sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return sql_query

# Example usage
english_query = "Show all employees with salary greater than $50000"
sql_query = translate_to_sql_select(english_query)
print("SQL Query:", sql_query)

📚 Documentation

Model Details

Property	Details
Model Name	T5 - SQL - Translator
Model Type	Text - to - Text Transformers
Base Model	Google T5 - small
Language	English
Task	English to SQL SELECT Translation
Training Data	Combination of English natural language queries paired with corresponding SQL SELECT queries from diverse domains.
Fine - tuning	The model has been fine - tuned on a dataset of English - to - SQL SELECT translations to optimize its performance for this specific task.

Example Use Cases

Automatically translate English questions into SQL SELECT queries for database querying.

Performance

Evaluation Metrics: BLEU score 34.962700

Acknowledgments

The original T5 model was developed by Google Research.
Training data was sourced from https://huggingface.co/datasets/b - mc2/sql - create - context
Special thanks to Hugging Face for providing the Transformers library and the Model Hub for easy model sharing.

📄 License

This project is licensed under the MIT license.

Contact

For any inquiries or issues regarding the model, feel free to contact:

thesuriya3@gmail.com

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