sample code update

README.md

@@ -60,6 +60,7 @@ model_id = "Rahmat82/t5-small-finetuned-summarization-xsum"
 
 model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
 tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True)
+summarizer = pipeline("summarization",model = model, tokenizer=tokenizer)
 
 text_to_summarize = """
 The koala is regarded as the epitome of cuddliness. However, animal lovers
@@ -73,8 +74,8 @@ within a decade. That is a shockingly fast decline." He added that koalas risk
 "sliding toward extinction" 
 """
 
-pipe = pipeline("summarization",model = model, tokenizer=tokenizer)
-print(pipe(text_to_summarize)[0]["summary_text"])
+
+print(summarizer(text_to_summarize)[0]["summary_text"])
 ```
 ### Use model with optimum/onnxruntime - super fast:
 ```python
@@ -89,7 +90,8 @@ model_name = "Rahmat82/t5-small-finetuned-summarization-xsum"
 
 model = ORTModelForSeq2SeqLM.from_pretrained(model_name, export=True)
 tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
-summarizer = pipeline("summarization", model=model, device_map="auto", tokenizer=tokenizer, batch_size=12)
+summarizer = pipeline("summarization", model=model, tokenizer=tokenizer,
+                                       device_map="auto", batch_size=12)
 
 text_to_summarize = """
 The koala is regarded as the epitome of cuddliness. However, animal lovers