Update README.md

README.md

@@ -5,7 +5,7 @@ license: cc-by-nc-4.0
 
 ## ProkBERT-mini Model
 
-ProkBERT-mini-k6s1 is part of the ProkBERT family of genomic language models, specifically designed for microbiome applications. This model, optimized for DNA sequence analysis. This model can provide robust and high resolution solutions. 
+ProkBERT-mini-k6s1 is part of the ProkBERT family of genomic language models, specifically designed for microbiome applications. This model, optimized for DNA sequence analysis, can provide robust and high resolution solutions. 
 
 ## Simple Usage Example
 
@@ -22,7 +22,7 @@ tokenization_parameters = {
 }
 # Initialize the tokenizer and model
 tokenizer = ProkBERTTokenizer(tokenization_params=tokenization_parameters, operation_space='sequence')
-model = MegatronBertForMaskedLM.from_pretrained("nerualbioinfo/prokbert-mini-k6s1")
+model = MegatronBertForMaskedLM.from_pretrained("neuralbioinfo/prokbert-mini-k6s1")
 # Example DNA sequence
 sequence = 'ATGTCCGCGGGACCT'
 # Tokenize the sequence
@@ -152,7 +152,7 @@ except ImportError:
 
 *Promoter prediction performance metrics on a diverse test set. A comparative analysis of various promoter prediction tools, showcasing their performance across key metrics including accuracy, F1 score, MCC, sensitivity, and specificity.*
 
-### Evaluation on phage recognitation benchmark
+### Evaluation on phage recognition benchmark
 
 | method        |    L |   auc_class1 |      acc |       f1 |      mcc |   recall |   sensitivity |   specificity |   tn |   fp |   fn |   tp |    Np |    Nn |   eval_time |
 |:--------------|-----:|-------------:|---------:|---------:|---------:|---------:|--------------:|--------------:|-----:|-----:|-----:|-----:|------:|------:|------------:|