Update README.md

README.md

@@ -40,7 +40,7 @@ In our paper, we outline the steps taken to train this model and demonstrate its
 from transformers import pipeline
 
 # Load the pipeline
-model = pipeline("ner", model="farnazzeidi/ner-bert-law-model", aggregation_strategy='simple')
+model = pipeline("ner", model="farnazzeidi/ner-legalturk-bert-model", aggregation_strategy='simple')
 
 # Input text
 text = "Burada, Tebligat Kanunu ile VUK düzenlemesi ayrımına dikkat etmek gerekir."
@@ -55,8 +55,8 @@ print(predictions)
 ```python
 # Load model and tokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("farnazzeidi/ner-bert-law-model")
-model = AutoModelForTokenClassification.from_pretrained("farnazzeidi/ner-bert-law-model")
+tokenizer = AutoTokenizer.from_pretrained("farnazzeidi/ner-legalturk-bert-model")
+model = AutoModelForTokenClassification.from_pretrained("farnazzeidi/ner-legalturk-bert-model")
 
 text = "Burada, Tebligat Kanunu ile VUK düzenlemesi ayrımına dikkat etmek gerekir."
 inputs = tokenizer(text, return_tensors="pt")