Update README.md - minor change to trigger a gh-pages deploy

README.md

@@ -13,7 +13,9 @@ Retrieval using dense representations is provided via integration with Facebook'
 Pyserini is primarily designed to provide effective, reproducible, and easy-to-use first-stage retrieval in a multi-stage ranking architecture.
 Our toolkit is self-contained as a standard Python package and comes with queries, relevance judgments, pre-built indexes, and evaluation scripts for many commonly used IR test collections
 With Pyserini, it's easy to reproduce runs on a number of standard IR test collections!
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 A low-effort way to try things out is to look at our [online notebooks](https://github.com/castorini/anserini-notebooks), which will allow you to get started with just a few clicks.
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 For additional details, [our paper](https://dl.acm.org/doi/10.1145/3404835.3463238) in SIGIR 2021 provides a nice overview.