Update readme

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

README.md

@@ -1,6 +1,6 @@
 # Text Embedding with Transformers
 
-*author: Jael Gu*
+*author: [Jael Gu](https://github.com/jaelgu)*
 
 <br />
 
@@ -15,7 +15,7 @@ This operator is implemented with pretrained models from [Huggingface Transforme
 ## Code Example
 
 Use the pretrained model 'distilbert-base-cased'
-to generate a text embedding for the sentence "Hello, world.". 
+to generate a text embedding for the sentence "Hello, world.".
 
 *Write the pipeline*:
 
@@ -38,10 +38,10 @@ Create the operator via the following factory method
 
 ***model_name***: *str*
 
-The model name in string.
+​	The model name in string.
 The default model name is "bert-base-uncased".
 
-Supported model names:
+​	Supported model names:
 
 <details><summary>Albert</summary>
 
@@ -59,7 +59,7 @@ Supported model names:
 
   - facebook/bart-large
 </details>
-  
+
 <details><summary>Bert</summary>
 
   - bert-base-cased
@@ -82,9 +82,9 @@ Supported model names:
   - TurkuNLP/bert-base-finnish-uncased-v1
   - wietsedv/bert-base-dutch-cased
 </details>
-    
+
 <details><summary>BertGeneration</summary>
-   
+
   - google/bert_for_seq_generation_L-24_bbc_encoder
 </details>
 
@@ -101,7 +101,7 @@ Supported model names:
   - google/bigbird-pegasus-large-pubmed
   - google/bigbird-pegasus-large-bigpatent
 </details>
-  
+
 <details><summary>CamemBert</summary>
 
   - camembert-base
@@ -110,11 +110,11 @@ Supported model names:
 </details>
 
 <details><summary>Canine</summary>
-  
+
   - google/canine-s
   - google/canine-c
 </details>
-    
+
 <details><summary>Convbert</summary>
 
   - YituTech/conv-bert-base
@@ -229,7 +229,7 @@ Supported model names:
 
   - uw-madison/nystromformer-512
 </details>
-  
+
 <details><summary>Reformer</summary>
 
   - google/reformer-crime-and-punishment
@@ -281,7 +281,7 @@ Supported model names:
 
 <details><summary>XLNet</summary>
 
-  - xlnet-base-cased 
+  - xlnet-base-cased
   - xlnet-large-cased
 </details>
 
@@ -303,12 +303,11 @@ and then return text embedding in ndarray.
 
 ***text***: *str*
 
-The text in string.
+​	The text in string.
 
 
 **Returns**:
 
 *numpy.ndarray*
 
-The text embedding extracted by model.
-
+​	The text embedding extracted by model.