Rerankers is a lightweight library addressing challenges in document reranking by simplifying the integration process, empowering users to experiment with different methods easily. With a unified API, consistent input/output formats, and impressive performance, it offers a user-friendly solution to improve relevance and ranking of search results, driving innovation in information retrieval.
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Meet Rerankers: A Lightweight Python Library to Provide a Unified Way to Use Various Reranking Methods
In the world of information retrieval, document reranking can be a powerful but intimidating challenge for those unfamiliar with it. Meet Rerankers, a lightweight library that aims to simplify the process of trying out different reranking models, empowering users to experiment freely without fear of disrupting their existing workflows.
Key Advantages of Rerankers
Rerankers offers a user-friendly solution with a unified API, simplifying the integration process and enabling users to explore and experiment with different reranking methods with ease.
The library provides a straightforward API with consistent input/output formats, making it easy to swap between different methods. Despite its lightweight nature, rerankers delivers impressive performance, consistently improving the relevance and ranking of search results.
Rerankers is designed to address the challenges of document reranking by providing a unified API, simplifying the integration process, and delivering reliable and impressive performance.
Installation
Installation is very simple. The core package ships with just two dependencies, tqdm and pydantic, to avoid conflicts with your current environment. Users can then install only the dependencies required by the models they want to try out:
- Core package only, will require other dependencies already installed:
pip install rerankers - All transformers-based approaches (cross-encoders, t5, colbert):
pip install "rerankers[transformers]" - RankGPT:
pip install "rerankers[gpt]" - API-based rerankers (Cohere, Jina, soon MixedBread):
pip install "rerankers[api]" - All of the above:
pip install "rerankers[all]"
Practical AI Solution
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