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One of the questions we debated while training ModernBERT was whether a modern trained encoder would unlock zero-shot reasoning using only it's generative head? Spoilers: the answer is yes.

After instruction tuning on Flan, ModernBERT-Large-Instruct outperforms similarly sized LLMs on MMLU & MMLU-Pro, and achieves ~90 percent of Llama 3.2 1B's performance with ~65 percent fewer parameters.

Can all encoders be instruction-tuned? Can we replicate ModernBERT's results with an older model like RoBERTa or peer model like GTE-en-MLM? No. And it's not close.

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