Update

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

README.md

@@ -19,27 +19,19 @@ Use the pre-trained model "huggingface/CodeBERTa-small-v1"
 to generate text embeddings for given 
 text description "return max value" and code "def max(a,b): if a>b: return a else return b".
 
-*Write the pipeline*:
+*Write a pipeline with explicit inputs/outputs name specifications:*
 
 ```python
-import towhee
+from towhee.dc2 import pipe, ops, DataCollection
 
-(
-    towhee.dc(['find max value', 'def max(a,b): if a>b: return a else return b'])
-          .code_search.codebert(model_name='huggingface/CodeBERTa-small-v1')
+p = (
+    pipe.input('text')
+        .map('text', 'embedding', ops.code_search.codebert(model_name='huggingface/CodeBERTa-small-v1'))
+        .output('text', 'embedding')
 )
-```
-
-*Write a same pipeline with explicit inputs/outputs name specifications:*
 
-```python
-import towhee
-
-(
-    towhee.dc['text'](['return max value', 'def max(a,b): if a>b: return a else return b'])
-          .code_search.codebert['text', 'embedding']()
-          .show()
-)
+DataCollection(p('find max value')).show()
+DataCollection(p('def max(a,b): if a>b: return a else return b')).show()
 ```
 
 <img src="./result.png" width="800px"/>