update readme

README.md

@@ -1,4 +1,8 @@
 
+---
+license: apache-2.0
+---
+
 # HPD-TinyBERT-F128
 
 This repository contains the pre-trained models for our paper [Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation](https://arxiv.org/abs/2203.07687).
@@ -29,7 +33,7 @@ model = SentenceTransformer('Xuandong/HPD-TinyBERT-F128')
 
 Then you can use our model for **encoding sentences into embeddings**
 ```python
-sentences = ['He plays guitar.', 'A street vendor is outside.', 'A woman is reading.']
+sentences = ['He plays guitar.', 'A street vendor is outside.']
 sentence_embeddings = model.encode(sentences)
 
 for sentence, embedding in zip(sentences, sentence_embeddings):
@@ -42,13 +46,11 @@ for sentence, embedding in zip(sentences, sentence_embeddings):
 
 We evaluate our model on semantic textual similarity (STS) tasks. The results are:
 
-```
-+-------+-------+-------+-------+-------+--------------+-----------------+-------+
+
 | STS12 | STS13 | STS14 | STS15 | STS16 | STSBenchmark | SICKRelatedness |  Avg. |
-+-------+-------+-------+-------+-------+--------------+-----------------+-------+
+|-------|-------|-------|-------|-------|--------------|-----------------|-------|
 | 74.29 | 83.05 | 78.80 | 84.62 | 81.17 |    84.36     |      80.83      | 81.02 |
-+-------+-------+-------+-------+-------+--------------+-----------------+-------+
-```
+
 
 ## Training