Update README.md

README.md

@@ -5,7 +5,7 @@ license: mit
 ## TwiBERT
 ## Model Description
 TwiBERT is a pre-trained language model specifically designed for the Twi language, which is widely spoken in Ghana, 
-West Africa. This model boasts 61 million parameters, 6 attention heads, 768 hidden units, and a feed-forward size of 3072. 
+West Africa. This model has 61 million parameters, 6 layers, 6 attention heads, 768 hidden units, and a feed-forward size of 3072. 
 To optimize its performance, TwiBERT was trained using a combination of the Asanti Twi Bible and a dataset 
 sourced through crowdsourcing efforts. 
 
@@ -25,6 +25,6 @@ The example code below illustrates how you can use the TwiBERT model on a downtr
 
 ```python
 >>> from transformers import AutoTokenizer, AutoModelForTokenClassification
->>> model = AutoModelForTokenClassification.from_pretrained("sakrah/twibert")
->>> tokenizer = AutoTokenizer.from_pretrained("sakrah/twibert")
+>>> model = AutoModelForTokenClassification.from_pretrained("sakrah/TwiBERT")
+>>> tokenizer = AutoTokenizer.from_pretrained("sakrah/TwiBERT")
 ```