Update README.md

README.md

@@ -15,7 +15,7 @@ tags:
 
 This finetuned model is specifically designed for promoter identification and is based on the [ProkBERT-mini-long model](https://huggingface.co/neuralbioinfo/prokbert-mini-long). 
 
-For more details, refer to the [pahge dataset description](https://huggingface.co/datasets/neuralbioinfo/phage-test-10k) used for training and evaluating this model.
+For more details, refer to the [phage dataset description](https://huggingface.co/datasets/neuralbioinfo/phage-test-10k) used for training and evaluating this model.
 
 ### Example Usage
 
@@ -44,7 +44,7 @@ shift= 2
 tok_params = {'kmer' : kmer,
              'shift' : shift}
 tokenizer = ProkBERTTokenizer(tokenization_params=tok_params)
-model = BertForBinaryClassificationWithPooling.from_pretrained(finetuned_model)
+model = MegatronBertForSequenceClassification.from_pretrained(finetuned_model)
 sequence = 'CACCGCATGGAGATCGGCACCTACTTCGACAAGCTGGAGGCGCTGCTGAAGGAGTGGTACGAGGCGCGCGGGGGTGAGGCATGACGGACTGGCAAGAGGAGCAGCGTCAGCGC'
 inputs = tokenizer(sequence, return_tensors="pt")
 # Ensure that inputs have a batch dimension