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🚀 hybrid-search-eval - Evaluate Embedding Models Easily
📚 Introduction
Welcome to hybrid-search-eval! This application helps you benchmark embedding models in hybrid search scenarios, combining BM25 and vector search using Weaviate. It provides a user-friendly way to assess how well different models perform, making it easier for you to choose the right one for your needs.
🚀 Getting Started
To get started with hybrid-search-eval, follow these simple steps. You’ll need a computer connected to the internet. This guide will help you install the application so you can start benchmarking models right away.
🔍 System Requirements
Before downloading the application, ensure your system meets the following requirements:
- Operating System: Windows 10 or higher, macOS 10.13 or higher, or a recent version of Linux.
- RAM: Minimum 4 GB.
- Storage: At least 250 MB of free space.
- Internet Connection: Required for downloading the application and additional data.
💾 Download & Install
To download the latest version of hybrid-search-eval, please visit the following link:
On the Releases page, look for the latest version of the application. Click on the version number to see the available files. You will find different builds for various operating systems.
Installation Steps
- Visit the Releases Page: Click the link above to access the release files.
- Select Your Operating System: Choose the appropriate file for your system:
- For Windows, download the
.exefile. - For macOS, download the
.dmgfile. - For Linux, download the
.tar.gzor installation package.
- For Windows, download the
- Download the File: Click the link, and your download will begin. Save the file to your computer.
- Run the Installer:
- For Windows, double-click the downloaded
.exefile. - For macOS, open the
.dmgfile and drag the application to your Applications folder. - For Linux, unpack the tar file and run the setup command in your terminal.
- For Windows, double-click the downloaded
- Follow the Instructions: Follow on-screen instructions to complete the installation. If you run into any issues, consult the FAQ section below.
📊 Using the Application
Once installed, you can launch hybrid-search-eval. The application interface is straightforward. Here’s how to get started:
- Open the App: Find the application in your programs list or applications folder and double-click to open.
- Select Benchmarking Options: Choose the embedding models and the parameters you want to evaluate.
- Run the Evaluation: Click the “Start Evaluation” button to begin. The application will process the data and show you the results.
Understanding the Results
After an evaluation, you will see results presented in a clear format. Key metrics include:
- Mean Reciprocal Rank (MRR): A measure of how well the model ranks the correct answers.
- Precision and Recall: Indicators of how many relevant items are found and how many relevant items are retrieved.
- Execution Time: How long the evaluation took to complete.
Review these metrics to determine which model performs best for your use case.
❓ Frequently Asked Questions
Q: What is hybrid search?
A: Hybrid search combines traditional keyword-based search (like BM25) with vector search, which uses embeddings to find similar items in a more contextual manner.
Q: What are embeddings?
A: Embeddings are a way of representing words or phrases as vectors of numbers in a multi-dimensional space, allowing models to understand semantic meaning better.
Q: Can I use this tool without programming skills?
A: Yes! hybrid-search-eval is designed for users with no programming experience. The interface is user-friendly, and this guide provides complete instructions.
📞 Support
If you need help while using hybrid-search-eval, feel free to reach out. You can open an issue on the GitHub page or contact support through our community forum.
Experience efficient embedding model evaluations today!