Models like transformers have inherent limitations in counting elements beyond tokens, making it challenging for them to perform tasks like counting words in a sentence. To overcome this, contextual positional encoding (COPE) adds contextual information to help the model understand the position and context of words in a sentence, improving performance on coding tasks.
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