Update README.md

README.md

@@ -1,11 +1,11 @@
 ## t5-base-fine-tuned-on-jfleg
-T5-base model fine-tuned on the JFLEG dataset with the objective of **text2text-generation**.
+T5-base model fine-tuned on the [JFLEG dataset](https://huggingface.co/datasets/jfleg) with the objective of **text2text-generation**.
 
 # Model Description:
 T5 is an encoder-decoder model pre-trained with a multi-task mixture of unsupervised and supervised tasks and for which each task is converted into a text-to-text format.
 .T5 works well on a variety of tasks out-of-the-box by prepending a different prefix to the input corresponding to each task, e.g., for translation: translate English to German: …, for summarization: summarize: ….
 
-The T5 model was presented in **Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer** by Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu.
+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.
 
 ## Pre-Processing:
 For this task of grammar correction, we’ll use the prefix “grammar: “ to each of the input sentences.
@@ -15,7 +15,7 @@ Grammar: Your Sentence
 ```
 
 ## How to use :
-You can use this model directly with the pipeline for for detecting and correcting grammatical mistakes.
+You can use this model directly with the pipeline for detecting and correcting grammatical mistakes.
 
 ```
 from transformers import pipeline