Update README.md

README.md

@@ -45,7 +45,7 @@ This model builds on the RoBERTa architecture with a similar approach to our pap
     inputs = torch.tensor([tokenized_output], dtype=torch.long)
     
     # Load the pre-trained BigBird model
-    model = AutoModel.from_pretrained("MsAlEhR/MetaBERTa-bigbird-gene", output_hidden_states=True)
+    model = AutoModel.from_pretrained("MsAlEhR/MetaBerta-400-fragments-18k-genome", output_hidden_states=True)
     
     # Generate hidden states
     outputs = model(input_ids=inputs, attention_mask=attention_mask)