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@@ -37,6 +37,6 @@ and 24 layers; and SARITA-XL, with 1.2 billion parameters, featuring an embeddin
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  its unique role in protein structure and function. The tokenizer also includes special tokens like <PAD> for padding shorter sequences and <EOS> for marking sequence ends, ensuring consistency across datasets. This process reduces variability and enhances the model's ability to learn meaningful
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  patterns from protein sequences. At the end each token is transformed into a numerical representation using a look-up table
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- ![Symbol](./Symbol.png)
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  its unique role in protein structure and function. The tokenizer also includes special tokens like <PAD> for padding shorter sequences and <EOS> for marking sequence ends, ensuring consistency across datasets. This process reduces variability and enhances the model's ability to learn meaningful
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  patterns from protein sequences. At the end each token is transformed into a numerical representation using a look-up table
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+ ![Symbol](./Architecture.png)
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