Update README.md

README.md

@@ -81,6 +81,8 @@ pip install -U sentence-transformers
 ```
 
 Then you can load this model and run inference.
+
+#### Semantic Similarity:
 ```python
 from sentence_transformers import SentenceTransformer
 
@@ -104,6 +106,25 @@ print(similarities)
 #         [ 0.0078, -0.0407,  1.0000]])
 ```
 
+#### Doc/Query Embedding
+
+```python
+from sentence_transformers import CrossEncoder, util
+from transformers import AutoTokenizer, TFAutoModel
+
+# Load the bi-encoder
+tokenizer = AutoTokenizer.from_pretrained("/teamspace/studios/this_studio/secure_modern_bert/Models/reranker-securebert2-biencoder/final")
+model = TFAutoModel.from_pretrained("/teamspace/studios/this_studio/secure_modern_bert/Models/reranker-securebert2-biencoder/final")
+
+# Encode queries and documents
+query_embedding = model(tokenizer("Example query", return_tensors="tf"))[0]
+doc_embedding = model(tokenizer("Candidate document", return_tensors="tf"))[0]
+
+# Compute similarity
+import tensorflow as tf
+similarity = tf.keras.losses.cosine_similarity(query_embedding, doc_embedding)
+print(similarity)
+```
 
 ## Training Details