different api example

README.md

@@ -7,7 +7,7 @@ metrics:
 - accuracy (balanced)
 - F1 (weighted)
 widget:
-- text: "Covid-19 outbreaks raise concerns over more infectious strain"
+- text: "70-85% of the population needs to get vaccinated against the novel coronavirus to achieve herd immunity."
 
 ---
 
@@ -94,7 +94,7 @@ Freedom and Democracy          0.048608
 
 ## Limitations and bias
 
-The model was trained on sentences in political manifestos from parties in the 8 countries mentioned above between 1992-2019, manually annotated by the [Manifesto Project](https://manifesto-project.wzb.eu/information/documents/information). The model output therefore reproduces the limitations of the dataset in terms of country coverage, time span, domain definitions and potential biases of the annotators - as any supervised machine learning model would. Applying the model to other types of data (other types of texts, countries etc.) probably reduces performance. 
+The model was trained on sentences in political manifestos from parties in the 8 countries mentioned above between 1992-2019, manually annotated by the [Manifesto Project](https://manifesto-project.wzb.eu/information/documents/information). The model output therefore reproduces the limitations of the dataset in terms of country coverage, time span, domain definitions and potential biases of the annotators - as any supervised machine learning model would. Applying the model to other types of data (other types of texts, countries etc.) will reduce performance. 
 
 
 ### BibTeX entry and citation info
@@ -104,6 +104,6 @@ The model was trained on sentences in political manifestos from parties in the 8
   title={Policy-DistilBERT},
   author={Moritz Laurer},
   year={2020},
-  note = {Unpublished paper}
+  note={Unpublished paper}
 }
 ```