Squash typo

README.md

@@ -22,7 +22,7 @@ It is a BERT model (Devlin et al. 2019) although the typical Next Sentence Predi
 This architecture has subsequently been finetuned for semantic search purposes. We have followed the procedure proposed by [S-BERT](https://www.sbert.net/examples/applications/semantic-search/README.html).
 
 ### What is the output of the model?
-The model returns an embddding vector of 768 dimensions for each function that it's given. These embeddings can be compared to
+The model returns an embedding vector of 768 dimensions for each function that it's given. These embeddings can be compared to
 get an indication of which functions are similar to each other.
 
 ### How does the model perform?