Update README.md

README.md

@@ -27,8 +27,8 @@ For more details, check out our [example.com](paper)
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
-model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
+tokenizer = AutoTokenizer.from_pretrained("dru-ac/ArGTClass")
+model = AutoModelForSequenceClassification.from_pretrained("dru-ac/ArGTClass", device_map = 'auto')
 
 text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
@@ -43,8 +43,8 @@ predicted_class = model.config.id2label[ind.item()]
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 
-tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
-model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
+tokenizer = AutoTokenizer.from_pretrained("dru-ac/ArGTClass")
+model = AutoModelForSequenceClassification.from_pretrained("dru-ac/ArGTClass", device_map = 'auto')
 
 text = " .قصفت إسرائيل مستشفى المعمداني في مدينة غزة، والذي خلف مئات الشهداء والجرحى"
 
@@ -58,9 +58,9 @@ predicted_class = model.config.id2label[ind.item()]
 ### Pipeline example
 
 ```python
-from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
-tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
-model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+tokenizer = AutoTokenizer.from_pretrained("dru-ac/ArGTClass")
+model = AutoModelForSequenceClassification.from_pretrained("dru-ac/ArGTClass", device_map = 'auto')
 
 classifier = pipeline("text-classification", model=model, tokenizer= tokenizer)
 
@@ -73,9 +73,9 @@ classifier(text)
 ### Pipeline example (GPU)
 
 ```python
-from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
-tokenizer = AutoTokenizer.from_pretrained("dru-acrps/ArGTClass")
-model = AutoModelForSequenceClassification.from_pretrained("dru-acrps/ArGTClass", device_map = 'auto')
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+tokenizer = AutoTokenizer.from_pretrained("dru-ac/ArGTClass")
+model = AutoModelForSequenceClassification.from_pretrained("dru-ac/ArGTClass", device_map = 'auto')
 
 classifier = pipeline("text-classification", model=model, tokenizer= tokenizer, device="cuda:0")