Update README.md

README.md

@@ -19,9 +19,6 @@ Pretrained model on English language using a masked language modeling (MLM) obje
 [this repository](https://github.com/google-research/bert). This model is uncased: it does not make a difference
 between english and English.
 
-Disclaimer: The team releasing BERT did not write a model card for this model so this model card has been written by
-the Hugging Face team.
-
 ## Model description
 
 Please, refer to the [original model card](https://huggingface.co/bert-base-uncased) for more details on bert-base-uncased.
@@ -42,7 +39,7 @@ from transformers import BertTokenizer
 import mlx.core as mx
 
 model = create_model("bert-base-uncased") # it will download weights from this repository
-tokenizer = BertTokenizer.from_pretrained("bert-large-uncased")
+tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
 
 batch = ["This is an example of BERT working on MLX."]
 tokens = tokenizer(batch, return_tensors="np", padding=True)