Update README.md

README.md

@@ -27,8 +27,8 @@ You can use this model with Transformers *pipeline* for NER.
 ```python
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 from transformers import pipeline
-tokenizer = AutoTokenizer.from_pretrained("Davlan/distilbert-base-multilingual-cased-ner-hrl")
-model = AutoModelForTokenClassification.from_pretrained("Davlan/distilbert-base-multilingual-cased-ner-hrl")
+tokenizer = AutoTokenizer.from_pretrained("LukeGPT88/distilbert-base-multilingual-cased-ner-hrl")
+model = AutoModelForTokenClassification.from_pretrained("LukeGPT88/distilbert-base-multilingual-cased-ner-hrl")
 nlp = pipeline("ner", model=model, tokenizer=tokenizer)
 example = "Nader Jokhadar had given Syria the lead with a well-struck header in the seventh minute."
 ner_results = nlp(example)