Update README.md

README.md

@@ -6,18 +6,29 @@ The original Google's [**T5-base**] model was pre-trained on [**C4 dataset**](ht
 
 The T5 model was presented in [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer**](https://arxiv.org/pdf/1910.10683.pdf) by Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu.
 
+# Prefix:
+The T-5 model use "grammar: " as the input text prefix for grammatical corrections.
+
 ## Usage :
 ```
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-  
-tokenizer = AutoTokenizer.from_pretrained("team-writing-assistant/t5-base-c4jfleg")
+from transformers import pipeline
+
+checkpoint = "team-writing-assistant/t5-base-c4jfleg"
+model = pipeline("text2text-generation", model=checkpoint)
+
+text = "Speed of light is fastest then speed of sound"
+text = "grammar: " + text
 
-model = AutoModelForSeq2SeqLM.from_pretrained("team-writing-assistant/t5-base-c4jfleg")
+output = model(text)
+print("Result: ", output[0]['generated_text'])
+```
+```
+Result: Speed of light is faster than speed of sound.
 ```
 
-## Examples :
+## Other Examples :
 Input: My grammar are bad.   
 Output: My grammar is bad.
 
-Input: Speed of light is fastest than speed of sound   
-Output: Speed of light is faster than speed of sound.
+Input: Who are the president?   
+Output: Who is the president?