Test.

README.md

@@ -26,11 +26,11 @@ pip install -U sentence-transformers
 
 Then you can use the model like this:
 
-```
+```python
 from sentence_transformers import SentenceTransformer
 sentences = ["This is an example sentence"]
 
-model = SentenceTransformer({example})
+model = SentenceTransformer(TODO)
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -38,7 +38,7 @@ print(embeddings)
 
 ## Usage (HuggingFace Transformers)
 
-```
+```python
 from transformers import AutoTokenizer, AutoModel
 import torch
 
@@ -65,7 +65,7 @@ encoded_input = tokenizer(sentences, padding=True, truncation=True, max_length=1
 with torch.no_grad():
     model_output = model(**encoded_input)
 
-#Perform pooling. In this case, max pooling.
+# Perform pooling. In this case, max pooling.
 sentence_embeddings = max_pooling(model_output, encoded_input['attention_mask'])
 
 print("Sentence embeddings:")

pytorch_model.bin

@@ -1,3 +1,3 @@
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