Add Sentence Transformers usage

README.md

@@ -3,6 +3,7 @@ language:
 - en
 tags:
 - ColBERT
+- multi-vector
 - PyLate
 - sentence-transformers
 - sentence-similarity
@@ -783,6 +784,40 @@ This model is a lightweight, 17 million parameter ColBERT with a projection dime
 
 ## 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("mixedbread-ai/mxbai-edge-colbert-v0-17m")
+
+query = "Which planet is known as the Red Planet?"
+documents = [
+    "Venus is often called Earth's twin because of its similar size and proximity.",
+    "Mars, known for its reddish appearance, is often referred to as the Red Planet.",
+    "Jupiter, the largest planet in our solar system, has a prominent red spot.",
+    "Saturn, famous for its rings, is sometimes mistaken for the Red Planet.",
+]
+
+query_embeddings = model.encode_query(query)
+document_embeddings = model.encode_document(documents)
+print(query_embeddings.shape, document_embeddings[0].shape)
+# (12, 48) (18, 48)
+
+# MaxSim late-interaction scoring (higher is more relevant)
+scores = model.similarity(query_embeddings, document_embeddings)
+print(scores)
+# tensor([[11.5693, 11.7584, 11.7099, 11.7229]])
+```
+
+### PyLate
+
 To use this model, you first need to install PyLate:
 
 via uv