Update README.md

README.md

@@ -61,15 +61,15 @@ This model can be used to determine the sentiment of a text with three possible
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-Pre-trained = "hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier"
-tokenizer = AutoTokenizer.from_pretrained(Pre-trained)
-model = AutoModelForSequenceClassification.from_pretrained(Pre-trained)
+modelName = "hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier"
+tokenizer = AutoTokenizer.from_pretrained(modelName)
+model = AutoModelForSequenceClassification.from_pretrained(modelName)
 ```
 ### make classification
 ```python
 from transformers import pipeline
-pretrained_name = "hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier"
-class_model = pipeline(tokenizer=pretrained_name, model=pretrained_name)
+modelName = "hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier"
+class_model = pipeline(tokenizer=modelName, model=modelName)
 
 test_data = "buku ini jelek sekali"
 class_model(test_data)