Update README.md

README.md

@@ -3,21 +3,25 @@ language: en
 tags:
 - text-classification
 - sentiment-analysis
+- 'sentiment '
+- 'synthetic data '
 license: apache-2.0
 widget:
-- text: "I absolutely loved this movie! The acting was superb and the plot was engaging."
-  example_title: "Very Positive Review"
-- text: "The service at this restaurant was terrible. I'll never go back."
-  example_title: "Very Negative Review"
-- text: "The product works as expected. Nothing special, but it gets the job done."
-  example_title: "Neutral Review"
-- text: "I'm somewhat disappointed with my purchase. It's not as good as I hoped."
-  example_title: "Negative Review"
-- text: "This book changed my life! I couldn't put it down and learned so much."
-  example_title: "Very Positive Review"
+- text: >-
+    I absolutely loved this movie! The acting was superb and the plot was
+    engaging.
+  example_title: Very Positive Review
+- text: The service at this restaurant was terrible. I'll never go back.
+  example_title: Very Negative Review
+- text: The product works as expected. Nothing special, but it gets the job done.
+  example_title: Neutral Review
+- text: I'm somewhat disappointed with my purchase. It's not as good as I hoped.
+  example_title: Negative Review
+- text: This book changed my life! I couldn't put it down and learned so much.
+  example_title: Very Positive Review
 inference:
   parameters:
-    temperature: 1.0
+    temperature: 1
 pipeline_tag: text-classification
 ---
 # BERT-based Sentiment Classification Mode