Update README.md

README.md

@@ -55,7 +55,7 @@ labels = [row[1] for row in csvreader if len(row) > 1]
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
 model.save_pretrained(MODEL)
 
-text = "Good night 😊"
+text = "NIO"
 text = preprocess(text)
 encoded_input = tokenizer(text, return_tensors='pt')
 output = model(**encoded_input)
@@ -66,7 +66,7 @@ scores = softmax(scores)
 # model = TFAutoModelForSequenceClassification.from_pretrained(MODEL)
 # model.save_pretrained(MODEL)
 
-# text = "Good night 😊"
+# text = "NIO"
 # encoded_input = tokenizer(text, return_tensors='tf')
 # output = model(encoded_input)
 # scores = output[0][0].numpy()
@@ -87,4 +87,4 @@ Output:
 1) positive 0.8466
 2) neutral 0.1458
 3) negative 0.0076
-```
+```