Update README.md

README.md

@@ -8,6 +8,28 @@ tags:
 - structured-data-search
 ---
 A Siamese BERT architecture trained at character levels tokens for embedding based Fuzzy matching.
+
+
+## Usage (Sentence-Transformers)
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+```
+pip install -U sentence-transformers
+```
+Then you can use the model like this:
+```python
+from sentence_transformers import SentenceTransformer, util
+word1 = "fuzzformer"
+word1 = " ".join([char for char in word1]) ## divide the word to char level to fuzzy match
+word2 = "fizzformer"
+word2 = " ".join([char for char in word2]) ## divide the word to char level to fuzzy match
+words = [word1, word2]
+
+model = SentenceTransformer('shahrukhx01/paraphrase-mpnet-base-v2-fuzzy-matcher')
+fuzzy_embeddings = model.encode(words)
+
+print("Fuzzy Match score:")
+print(util.cos_sim(fuzzy_embeddings[0], fuzzy_embeddings[1]))
+```
 ```python
 import torch
 from transformers import AutoTokenizer, AutoModel