Update README.md

README.md

@@ -2,7 +2,7 @@
 language: en
 tags:
 - qa
-- question 
+- question
 - generation
 - SQuAD
 - data2text
@@ -15,7 +15,7 @@ datasets:
 model-index:
 - name: t5-qg_webnlg_synth-en
   results:
-  - task: 
+  - task:
       name: Data Question Generation
       type: Text To Text Generation
 widget:
@@ -41,7 +41,7 @@ You can play with the model using the inference API, the text input format shoul
 
 `text_input = "{ANSWER} </s> {CONTEXT}"`
 
-where CONTEXT is a structured table that is linearised this way:
+where `CONTEXT is a structured table that is linearised this way:
 
 `CONTEXT = "name [ The Eagle ] , eatType [ coffee shop ] , food [ French ] , priceRange [ £ 2 0 - 2 5 ]"`
 
@@ -54,9 +54,8 @@ The model was trained on synthetic data as described in [Data-QuestEval: A Refer
 ```bibtex
 @article{rebuffel2021data,
   title={Data-QuestEval: A Referenceless Metric for Data to Text Semantic Evaluation},
-  author={Rebuffel, Cl{\\\\'e}ment and Scialom, Thomas and Soulier, Laure and Piwowarski, Benjamin and Lamprier, Sylvain and Staiano, Jacopo and Scoutheeten, Geoffrey and Gallinari, Patrick},
+  author={Rebuffel, Cl{\'{e}}ment and Scialom, Thomas and Soulier, Laure and Piwowarski, Benjamin and Lamprier, Sylvain and Staiano, Jacopo and Scoutheeten, Geoffrey and Gallinari, Patrick},
   journal={arXiv preprint arXiv:2104.07555},
   year={2021}
 }
-}
 ```