Update README.md

README.md

@@ -21,6 +21,17 @@ model-index:
             type: accuracy
             value: 0.9316
 ---
+## How to Get Started with the Model
+
+Use the code below to get started with the model:
+
+```python
+from transformers import pipeline,DistilBertTokenizer
+
+tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")
+classifier = pipeline("sentiment-analysis", model="3oclock/distilbert-imdb", tokenizer=tokenizer)
+result = classifier("I love this movie!")
+print(result)
 
 # Model Card for DistilBERT Fine-Tuned on IMDb Dataset
 
@@ -74,16 +85,4 @@ The model was trained on a dataset of movie reviews, so it may not perform as we
 
 ### Recommendations
 
-Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model:
-
-```python
-from transformers import pipeline,DistilBertTokenizer
-
-tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")
-classifier = pipeline("sentiment-analysis", model="3oclock/distilbert-imdb", tokenizer=tokenizer)
-result = classifier("I love this movie!")
-print(result)
+Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model.