Update README

README.md

@@ -20,7 +20,7 @@ _This model is a quantized version of the base model. It's using 10x256 Product
 ```python
 from staticvectors import StaticVectors
 
-model = StaticVectors("neuml/word2vec")
+model = StaticVectors("neuml/word2vec-quantized")
 model.embeddings(["word"])
 ```
 
@@ -29,6 +29,6 @@ Given that pre-trained embeddings models can get quite large, there is also a SQ
 ```python
 from staticvectors import StaticVectors
 
-model = StaticVectors("neuml/word2vec/model.sqlite")
+model = StaticVectors("neuml/word2vec-quantized/model.sqlite")
 model.embeddings(["word"])
 ```