From f94238bd99bd029c316c79158923d547404f993b Mon Sep 17 00:00:00 2001
From: Matheus Cerqueira <36471202+CerqueiraMatheus@users.noreply.github.com>
Date: Sun, 23 Apr 2023 21:16:14 -0300
Subject: [PATCH] Update README.rst

Fix small typo on multilingual (previously muliglingual)
---
 README.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.rst b/README.rst
index e141ae8..753128c 100644
--- a/README.rst
+++ b/README.rst
@@ -52,7 +52,7 @@ support topic modeling. See the papers for details:
 Topic Modeling with Contextualized Embeddings
 ---------------------------------------------
 
-Our new topic modeling family supports many different languages (i.e., the one supported by HuggingFace models) and comes in two versions: **CombinedTM** combines contextual embeddings with the good old bag of words to make more coherent topics; **ZeroShotTM** is the perfect topic model for task in which you might have missing words in the test data and also, if trained with muliglingual embeddings, inherits the property of being a multilingual topic model!
+Our new topic modeling family supports many different languages (i.e., the one supported by HuggingFace models) and comes in two versions: **CombinedTM** combines contextual embeddings with the good old bag of words to make more coherent topics; **ZeroShotTM** is the perfect topic model for task in which you might have missing words in the test data and also, if trained with multilingual embeddings, inherits the property of being a multilingual topic model!
 
 The big advantage is that you can use different embeddings for CTMs. Thus, when a new
 embedding method comes out you can use it in the code and improve your results. We are not limited