Update README.md

README.md

@@ -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-k6s2")
+model = MegatronBertForMaskedLM.from_pretrained("nerualbioinfo/prokbert-mini-k6s1")
 # Example DNA sequence
 sequence = 'ATGTCCGCGGGACCT'
 # Tokenize the sequence
@@ -52,6 +52,11 @@ outputs = model(**inputs)
 | Layers               | 6                                    |
 | Attention Heads      | 6                                    |
 
+### Intended Use
+
+**Intended Use Cases:** ProkBERT-mini-k6-s1 is intended for bioinformatics researchers and practitioners focusing on genomic sequence analysis, including:
+- sequence classification tasks
+- Exploration of genomic patterns and features
 
 ## Segmentation and Tokenization in ProkBERT Models