From e03129ad447ad7670fcc6206e5eb27a5435d4d86 Mon Sep 17 00:00:00 2001
From: Julien Chaumond <chaumond@gmail.com>
Date: Fri, 6 Mar 2020 18:07:44 -0500
Subject: [PATCH] [model_cards] Small formatting fix

cc @mrm8488
---
 .../mrm8488/bert-multi-cased-finetuned-xquadv1/README.md      | 4 +++-
 .../mrm8488/bert-multi-uncased-finetuned-xquadv1/README.md    | 4 ++++
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/model_cards/mrm8488/bert-multi-cased-finetuned-xquadv1/README.md b/model_cards/mrm8488/bert-multi-cased-finetuned-xquadv1/README.md
index 55b5b3e9c0..93b734a1cb 100644
--- a/model_cards/mrm8488/bert-multi-cased-finetuned-xquadv1/README.md
+++ b/model_cards/mrm8488/bert-multi-cased-finetuned-xquadv1/README.md
@@ -50,7 +50,8 @@ for the other languages.
 Citation:
 
 <details>
-```
+
+```bibtex
 @article{Artetxe:etal:2019,
       author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
       title     = {On the cross-lingual transferability of monolingual representations},
@@ -61,6 +62,7 @@ Citation:
       eprint    = {1910.11856}
 }
 ```
+
 </details>
 
 I used `Data augmentation techniques` and splited the dataset in order to have a train and test set. The test set was created in a way that contains the same number of samples for each language. Finally, I got:
diff --git a/model_cards/mrm8488/bert-multi-uncased-finetuned-xquadv1/README.md b/model_cards/mrm8488/bert-multi-uncased-finetuned-xquadv1/README.md
index a6a152a398..fed8159163 100644
--- a/model_cards/mrm8488/bert-multi-uncased-finetuned-xquadv1/README.md
+++ b/model_cards/mrm8488/bert-multi-uncased-finetuned-xquadv1/README.md
@@ -50,6 +50,8 @@ for the other languages.
 Citation:
 
 <details>
+
+```bibtex
 @article{Artetxe:etal:2019,
       author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
       title     = {On the cross-lingual transferability of monolingual representations},
@@ -59,6 +61,8 @@ Citation:
       archivePrefix = {arXiv},
       eprint    = {1910.11856}
 }
+```
+
 </details>
 
 I used `Data augmentation techniques` to obtain more samples and splited the dataset in order to have a train and test set. The test set was created in a way that contains the same number of samples for each language. Finally, I got: