Update README.md

README.md

@@ -22,14 +22,12 @@ model-index:
       value: 0.776119403
 
 widget:
-- text: "Is this review positive or negative? Review: Best cast iron skillet you will ever buy."
-  example_title: "Sentiment analysis"
-- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had ..."
-  example_title: "Coreference resolution"
-- text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book ..."
-  example_title: "Logic puzzles"
-- text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night ..."
-  example_title: "Reading comprehension"
+- text: "Vous ne devais pas y aller... vous ne sortirai pas vivantes"
+  example_title: "Mort implicite"
+- text: "Les morts ne parlent pas"
+  example_title: "Mort explicite 1"
+- text: "Les ambulances garées, le cortège des defunts, les cadavres qui sortaient de dessous les décombres"
+  example_title: "Mort explicite"
   
 license: agpl-3.0
 
@@ -38,7 +36,8 @@ license: agpl-3.0
 ## Description
 
 This model was built to compute detect the lexical field of death. It's main purpose was to automate annotation on a specific dataset. 
-There is no waranty that it  will work on any others dataset. We finetune, the camembert-base model using this code; https://github.com/psycholinguistics2125/train_NER.
+There is no waranty that it  will work on any others dataset. 
+We finetune, the camembert-base model using this code; https://github.com/psycholinguistics2125/train_NER.
 
 
 | Feature | Description |