Update README.md

README.md

@@ -27,17 +27,6 @@ widget:
     "other": 5
 }
 
-## How to Use:
-
-Here is an example of how to use this model for inference:
-
-```python
-from transformers import pipeline
-
-classifier = pipeline("text-classification", model="dnzblgn/Customer-Reviews-Classification")
-result = classifier("The product arrived on time and was exactly as described.")
-print(result)
-
 ### Model Description
 
 This fine-tuned DistilBERT model is specifically designed for document classification. It classifies customer feedback into six predefined categories: Shipping and Delivery, Customer Service, Price and Value, Quality and Performance, Use and Design, and Other. By leveraging the transformer-based architecture of DistilBERT, the model efficiently handles the syntactic patterns of text, providing accurate document classification based on content, style, and structure.
@@ -87,4 +76,15 @@ Recall: 0.948
 F1-Score: 0.948
 
 
-### For access to the synthetic dataset used, please contact: [deniz.bilgin@uni-konstanz.de].
+### For access to the synthetic dataset used, please contact: [deniz.bilgin@uni-konstanz.de].
+
+## How to Use:
+
+Here is an example of how to use this model for inference:
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="dnzblgn/Customer-Reviews-Classification")
+result = classifier("The product arrived on time and was exactly as described.")
+print(result)