bm25s
BM25S uses Scipy sparse matrices for efficient BM25 text ranking in Python, surpassing traditional tools in speed. The library requires just Scipy and Numpy, with optional features such as stemming. The latest updates include Numba backend for enhanced performance on large datasets. It offers memory-efficient data retrieval and integrates with Hugging Face model hub for cloud-based model management. Its flexible API allows for customizable tokenization and support for different BM25 variations, ensuring broad applicability.
