Update README.md

README.md

@@ -29,7 +29,7 @@ You can use this model directly with a pipeline for masked language modeling:
 
 ```python
 >>> from transformers import pipeline
->>> unmasker = pipeline('fill-mask', model='aioxlabs/bert-bantu')
+>>> unmasker = pipeline('fill-mask', model='nairaxo/bantu-bert')
 >>> unmasker("rais wa [MASK] ya tanzania.")
 
 
@@ -39,8 +39,8 @@ Here is how to use this model to get the features of a given text in PyTorch:
 
 ```python
 from transformers import BertTokenizer, BertModel
-tokenizer = BertTokenizer.from_pretrained('aioxlabs/bert-bantu')
-model = BertModel.from_pretrained("aioxlabs/bert-bantu")
+tokenizer = BertTokenizer.from_pretrained('nairaxo/bantu-bert')
+model = BertModel.from_pretrained("nairaxo/bantu-bert")
 text = "Replace me by any text you'd like."
 encoded_input = tokenizer(text, return_tensors='pt')
 output = model(**encoded_input)
@@ -50,8 +50,8 @@ and in TensorFlow:
 
 ```python
 from transformers import BertTokenizer, TFBertModel
-tokenizer = BertTokenizer.from_pretrained('aioxlabs/bert-bantu')
-model = TFBertModel.from_pretrained("aioxlabs/bert-bantu")
+tokenizer = BertTokenizer.from_pretrained('nairaxo/bantu-bert')
+model = TFBertModel.from_pretrained("nairaxo/bantu-bert")
 text = "Replace me by any text you'd like."
 encoded_input = tokenizer(text, return_tensors='tf')
 output = model(encoded_input)