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 [![Build Status](https://travis-ci.org/ThoughtRiver/lmdb-embeddings.svg?branch=master)](https://travis-ci.org/ThoughtRiver/lmdb-embeddings)
 
 # LMDB Embeddings
-Query word vectors (embeddings) very quickly with very little querying time overhead and far less memory usage than gensim or other equivalent solutions. This is made possible by [Lightning Memory-Mapped Database](https://en.wikipedia.org/wiki/Lightning_Memory-Mapped_Database).
+Query word vectors (embeddings) extremely quickly with very little overhead and far less memory usage than gensim or other equivalent solutions. This is made possible by [Lightning Memory-Mapped Database](https://en.wikipedia.org/wiki/Lightning_Memory-Mapped_Database).
 
 Inspired by [Delft](https://github.com/kermitt2/delft). As explained in their readme, this approach permits us to have the pre-trained embeddings immediately "warm" (no load time), to free memory and to use any number of embeddings similtaneously with a very negligible impact on runtime when using SSD.