  We present Spacerini, a tool that integrates the Pyserini toolkit for
reproducible information retrieval research with Hugging Face to enable the
seamless construction and deployment of interactive search engines. Spacerini
makes state-of-the-art sparse and dense retrieval models more accessible to
non-IR practitioners while minimizing deployment effort. This is useful for NLP
researchers who want to better understand and validate their research by
performing qualitative analyses of training corpora, for IR researchers who
want to demonstrate new retrieval models integrated into the growing Pyserini
ecosystem, and for third parties reproducing the work of other researchers.
Spacerini is open source and includes utilities for loading, preprocessing,
indexing, and deploying search engines locally and remotely. We demonstrate a
portfolio of 13 search engines created with Spacerini for different use cases.
