Update README.md

README.md

@@ -3,6 +3,7 @@ tags:
 - mteb
 - sentence-similarity
 - sentence-transformers
+- Sentence Transformers
 model-index:
 - name: gte-small 
   results:
@@ -2637,7 +2638,7 @@ We compared the performance of the GTE models with other popular text embedding
 
 Code example
 
-```
+```python
 import torch.nn.functional as F
 from torch import Tensor
 from transformers import AutoTokenizer, AutoModel
@@ -2669,6 +2670,18 @@ scores = (embeddings[:1] @ embeddings[1:].T) * 100
 print(scores.tolist())
 ```
 
+Use with sentence-transformers:
+```python
+from sentence_transformers import SentenceTransformer
+from sentence_transformers.util import cos_sim
+
+sentences = ['That is a happy person', 'That is a very happy person']
+
+model = SentenceTransformer('thenlper/gte-large')
+embeddings = model.encode(sentences)
+print(cos_sim(embeddings[0], embeddings[1]))
+```
+
 ### Limitation
 
 This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.