Update README.md

README.md

@@ -41,3 +41,25 @@ model = ClassificationModel(
 | 1| 0.0092 |
 | 2| 0.0087 |
 | 3| 0.0054 |
+
+### Nasıl Kullanılacağı
+
+```
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+tokenizer = AutoTokenizer.from_pretrained("Gorengoz/bert-turkish-sentiment-analysis-cased")
+model = AutoModelForSequenceClassification.from_pretrained("Gorengoz/bert-turkish-sentiment-analysis-cased")
+
+nlp=pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+code_to_label={
+
+'LABEL_0': 'olumlu ',
+
+'LABEL_1': 'nötr ',
+
+'LABEL_2': 'olumsuz' }
+
+code_to_label[nlp("Ürün berbat, paranıza yazık olur.")[0]['label']]
+
+```