Update README.md

README.md

@@ -18,10 +18,10 @@ The output dimension is 256, and the vocabulary size is 10.000.
 The training process used a mix of English (10%) and Portuguese (90%) texts.
 
 ```python
-from sentence_transformers import SentenceTransformer
+from model2vec import StaticModel
 
 # Load a pretrained Sentence Transformer model
-model = SentenceTransformer("cnmoro/custom-model2vec-tokenlearn-small")
+model = StaticModel.from_pretrained("cnmoro/custom-model2vec-tokenlearn-small")
 
 # Compute text embeddings
 embeddings = model.encode(["Example sentence"])