Add Sentence Transformers usage

README.md

@@ -1,6 +1,7 @@
 ---
 tags:
 - ColBERT
+- multi-vector
 - PyLate
 - sentence-transformers
 - sentence-similarity
@@ -204,6 +205,40 @@ ColBERT(
 
 ## Usage
 
+### Sentence Transformers
+
+This model can be used with [Sentence Transformers](https://www.sbert.net/) as a multi-vector (ColBERT-style late interaction) retriever via the `MultiVectorEncoder`:
+
+```bash
+pip install "sentence-transformers>=6.0.0"
+```
+
+```python
+from sentence_transformers import MultiVectorEncoder
+
+model = MultiVectorEncoder("lightonai/mLateOn")
+
+query = "Which planet is the Red Planet?"
+documents = [
+    "Mars, known for its reddish appearance, is often referred to as the Red Planet.",
+    "Mars, connu pour son apparence rougeâtre, est souvent appelé la planète rouge.",
+    "Mars, bekannt für sein rötliches Erscheinungsbild, wird oft als der Rote Planet bezeichnet.",
+    "Venus is often called Earth's twin because of its similar size and proximity.",
+]
+
+query_embeddings = model.encode_query(query)
+document_embeddings = model.encode_document(documents)
+print(query_embeddings.shape, document_embeddings[0].shape)
+# (10, 128) (20, 128)
+
+# MaxSim late-interaction scoring (higher is more relevant)
+scores = model.similarity(query_embeddings, document_embeddings)
+print(scores)
+# tensor([[9.6029, 9.5838, 9.5877, 9.4578]])
+```
+
+### PyLate
+
 First install the PyLate library:
 
 ```bash