Update README.md

README.md

@@ -40,13 +40,22 @@ pipeline_tag: text-classification
 ## Uses
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-  This model is designed for sentiment analysis tasks, allowing users to classify text into various emotional labels such as sadness, happiness, anger, and others. 
-  It is suitable for applications in customer feedback analysis, social media monitoring, and mental health assessments, providing valuable insights into emotional responses.
-  **Foreseeable Users:**
-    **Developers:** Those looking to integrate sentiment analysis into applications or services.
-    **Researchers:** Academics studying emotional expressions in text data or working on NLP projects.
-    **Businesses:** Companies wanting to analyze customer feedback or social media sentiment to improve products and services.
-    **Mental Health Professionals:** Practitioners who can use the model to gauge emotional states based on textual data.
+
+This model is designed for sentiment analysis tasks, allowing users to classify text into various emotional labels such as sadness, happiness, anger, and others. It is suitable for applications in customer feedback analysis, social media monitoring, and mental health assessments, providing valuable insights into emotional responses.
+
+**Foreseeable Users:**
+
+**Developers:**  
+Those looking to integrate sentiment analysis into applications or services.
+
+**Researchers:**  
+Academics studying emotional expressions in text data or working on NLP projects.
+
+**Businesses:**  
+Companies wanting to analyze customer feedback or social media sentiment to improve products and services.
+
+**Mental Health Professionals:**  
+Practitioners who can use the model to gauge emotional states based on textual data.
 
 ### Direct Use