Add multilingual to the language tag

README.md

@@ -5,26 +5,28 @@ language:
 - fr
 - it
 - nl
+- multilingual
+license: mit
 tags:
 - punctuation prediction
 - punctuation
-datasets: 
+datasets:
 - wmt/europarl
 - SoNaR
-license: mit
-widget:
-- text: "Ho sentito che ti sei laureata il che mi fa molto piacere"
-  example_title: "Italian"
-- text: "Tous les matins vers quatre heures mon père ouvrait la porte de ma chambre"
-  example_title: "French"
-- text: "Ist das eine Frage Frau Müller"
-  example_title: "German"
-- text: "My name is Clara and I live in Berkeley California"
-  example_title: "English"  
-- text: "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat"
-  example_title: "Dutch"
 metrics:
 - f1
+widget:
+- text: Ho sentito che ti sei laureata il che mi fa molto piacere
+  example_title: Italian
+- text: Tous les matins vers quatre heures mon p�re ouvrait la porte de ma chambre
+  example_title: French
+- text: Ist das eine Frage Frau M�ller
+  example_title: German
+- text: My name is Clara and I live in Berkeley California
+  example_title: English
+- text: hervatting van de zitting ik verklaar de zitting van het europees parlement
+    die op vrijdag 17 december werd onderbroken te zijn hervat
+  example_title: Dutch
 ---
 
 
@@ -49,13 +51,13 @@ pip install deepmultilingualpunctuation
 from deepmultilingualpunctuation import PunctuationModel
 
 model = PunctuationModel(model="oliverguhr/fullstop-punctuation-multilingual-sonar-base")
-text = "My name is Clara and I live in Berkeley California Ist das eine Frage Frau Müller"
+text = "My name is Clara and I live in Berkeley California Ist das eine Frage Frau M�ller"
 result = model.restore_punctuation(text)
 print(result)
 ```
 
 **output**
-> My name is Clara and I live in Berkeley, California. Ist das eine Frage, Frau Müller?
+> My name is Clara and I live in Berkeley, California. Ist das eine Frage, Frau M�ller?
 
 
 ### Predict Labels 
@@ -63,7 +65,7 @@ print(result)
 from deepmultilingualpunctuation import PunctuationModel
 
 model = PunctuationModel(model="oliverguhr/fullstop-punctuation-multilingual-sonar-base")
-text = "My name is Clara and I live in Berkeley California Ist das eine Frage Frau Müller"
+text = "My name is Clara and I live in Berkeley California Ist das eine Frage Frau M�ller"
 clean_text = model.preprocess(text)
 labled_words = model.predict(clean_text)
 print(labled_words)
@@ -71,7 +73,7 @@ print(labled_words)
 
 **output**
 
-> [['My', '0', 0.99998856], ['name', '0', 0.9999708], ['is', '0', 0.99975926], ['Clara', '0', 0.6117834], ['and', '0', 0.9999014], ['I', '0', 0.9999808], ['live', '0', 0.9999666], ['in', '0', 0.99990165], ['Berkeley', ',', 0.9941764], ['California', '.', 0.9952892], ['Ist', '0', 0.9999577], ['das', '0', 0.9999678], ['eine', '0', 0.99998224], ['Frage', ',', 0.9952265], ['Frau', '0', 0.99995995], ['Müller', '?', 0.972517]]
+> [['My', '0', 0.99998856], ['name', '0', 0.9999708], ['is', '0', 0.99975926], ['Clara', '0', 0.6117834], ['and', '0', 0.9999014], ['I', '0', 0.9999808], ['live', '0', 0.9999666], ['in', '0', 0.99990165], ['Berkeley', ',', 0.9941764], ['California', '.', 0.9952892], ['Ist', '0', 0.9999577], ['das', '0', 0.9999678], ['eine', '0', 0.99998224], ['Frage', ',', 0.9952265], ['Frau', '0', 0.99995995], ['M�ller', '?', 0.972517]]