update the readme

README.md

@@ -9,6 +9,8 @@ tags:
 - tiny
 - feature-extraction
 - sentence-similarity
+- sentence-transformers
+- transformers
 
 license: mit
 widget:
@@ -46,3 +48,12 @@ def embed_bert_cls(text, model, tokenizer):
 print(embed_bert_cls('привет мир', model, tokenizer).shape)
 # (312,)
 ```
+
+Alternatively, you can use the model with `sentence_transformers`:
+```Python
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer('cointegrated/rubert-tiny2')
+sentences = ["привет мир", "hello world", "здравствуй вселенная"]
+embeddings = model.encode(sentences)
+print(embeddings)
+```