Update README.md

README.md

@@ -6,15 +6,6 @@ To evaluate this and other models on Twitter-specific data, please refer to the
 
 ## Example of classification
 
-# Preprocess text (username and link placeholders)
-def preprocess(text):
-    new_text = []
-    for t in text.split(" "):
-        t = '@user' if t.startswith('@') and len(t) > 1 else t
-        t = 'http' if t.startswith('http') else t
-        new_text.append(t)
-    return " ".join(new_text)
-
 ```python
 from transformers import AutoModelForSequenceClassification
 from transformers import TFAutoModelForSequenceClassification
@@ -24,6 +15,15 @@ from scipy.special import softmax
 import csv
 import urllib.request
 
+# Preprocess text (username and link placeholders)
+def preprocess(text):
+    new_text = []
+    for t in text.split(" "):
+        t = '@user' if t.startswith('@') and len(t) > 1 else t
+        t = 'http' if t.startswith('http') else t
+        new_text.append(t)
+    return " ".join(new_text)
+
 # Tasks:
 # emoji, emotion, hate, irony, offensive, sentiment
 # stance/abortion, stance/atheism, stance/climate, stance/feminist, stance/hillary