HuggingFace BAAI BGE Reranker v2 m3 Demo

Welcome to the HuggingFace BAAI BGE Reranker v2 m3 demo repository. This project showcases how to use the BGE Reranker model with Hugging Face transformers. It supports both local and Azure cloud environments, making it flexible for various use cases.

Table of Contents

1. Overview
2. Installation
3. Usage
4. Features
5. Topics
6. Contributing
7. License
8. Releases
9. Acknowledgments

Overview

The BGE Reranker v2 m3 leverages advanced AI techniques to improve the relevance of search results. By applying transformer models from Hugging Face, it enhances the ranking of documents based on user queries. This project is designed for developers, researchers, and anyone interested in AI applications.

Installation

To set up the BGE Reranker v2 m3, follow these steps:

1. Clone the repository:

   git clone https://github.com/TioAbiyyu/HuggingFace-BAAI--BGERerankerv2m3.git
   cd HuggingFace-BAAI--BGERerankerv2m3

2. Install the required packages:

   Ensure you have Python installed. Then, use pip to install the necessary libraries:

   pip install -r requirements.txt

3. Set up Azure (if using Azure):

   If you plan to use Azure, ensure you have an Azure account and follow the setup instructions provided in the Azure documentation.

Usage

To run the demo, execute the following command:

python demo.py

This command will start the application locally. You can then access it via your web browser at http://localhost:5000.

Azure Deployment

For Azure deployment, follow these steps:

1. Package your application.
2. Use the Azure CLI to deploy your application to the cloud.

Refer to the Azure documentation for detailed instructions.

Features

• Local and Cloud Support: Run the model on your local machine or deploy it on Azure.
• Easy Integration: Use Hugging Face transformers for seamless integration with existing projects.
• High Performance: The BGE Reranker v2 m3 offers improved ranking capabilities for better search results.
• Interactive Jupyter Notebooks: Explore the model's capabilities using Jupyter Notebooks provided in the repository.

Topics

This project covers various topics relevant to AI and machine learning, including:

• AI
• Azure
• BAAI
• BGE
• Hugging Face
• Jupyter Notebook
• M3
• Python
• Reranker
• Transformers
• v2

Contributing

We welcome contributions from the community. If you want to help improve this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your branch to your forked repository.
5. Submit a pull request.

Your contributions are valuable and help enhance the project.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Releases

For the latest updates and releases, visit our Releases section. Download the latest version and follow the installation instructions to get started.

Acknowledgments

We would like to thank the Hugging Face community for their contributions to the field of AI and machine learning. Their work has made projects like this possible.

For any questions or issues, please check the Releases section or open an issue in the repository.

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Feel free to explore, experiment, and enhance the BGE Reranker v2 m3. Your feedback and contributions will help us build a better tool for everyone in the AI community.