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title: SQL Generation | |
emoji: 🦀 | |
colorFrom: red | |
colorTo: gray | |
sdk: gradio | |
sdk_version: 5.9.1 | |
app_file: app.py | |
pinned: false | |
license: mit | |
# SQL Generation 🦀 | |
Welcome to the **SQL Generation** Gradio application! This tool leverages advanced machine learning models to assist in generating SQL queries based on natural language inputs. Whether you're a developer, data analyst, or just curious about SQL, this app aims to simplify the process of crafting SQL queries. | |
## Features | |
- **Natural Language to SQL**: Convert plain English descriptions into SQL queries. | |
- **Multiple Datasets**: Trained on diverse datasets to handle various SQL generation tasks. | |
- **User-Friendly Interface**: Built with Gradio for an intuitive and interactive experience. | |
## Installation | |
To run this application locally, ensure you have Python 3.10 or higher installed. Then, install the required dependencies: | |
```bash | |
pip install gradio transformers datasets | |
``` | |
## Usage | |
After installing the dependencies, you can start the application by running: | |
```bash | |
python app.py | |
``` | |
This will launch a local server. Open your browser and navigate to http://127.0.0.1:7860 to access the interface. | |
### Datasets Used | |
The model has been trained on the following datasets: | |
- b-mc2/sql-create-context: Provides context for SQL query generation. | |
- TuneIt/o1-python: Offers examples of Python code snippets. | |
- HuggingFaceFW/fineweb-2: Includes various language models for fine-tuning. | |
- sentence-transformers/embedding-training-data: Supplies data for training sentence embeddings. | |
## Model | |
The application utilizes the distilbert-base-uncased model from Hugging Face, known for its efficiency and performance in natural language processing tasks. | |
## License | |
This project is licensed under the MIT License. | |
## Acknowledgments | |
- **Gradio** for providing an easy-to-use interface for machine learning models. | |
- **Hugging Face** for hosting the pre-trained models and datasets. | |
- **Datasets** for offering a wide range of datasets for training and evaluation. | |
For more information, refer to the **Gradio** documentation. |