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A head-to-head benchmark comparison of TransfoRNN(d=1024)(2-layer) (PTB) across 0 evaluations.
In this paper, we describe the use of recurrent neural networks to capture sequential information from the self-attention representations to improve the Transfo.
Full TransfoRNN(d=1024)(2-layer) (PTB) specs →No shared benchmark scores found for these models yet.
This comparison covers 0 benchmarks on which at least one of the selected models has a published score.
Scores are aggregated from official model cards, technical reports and standard public evaluations, and link back to each benchmark's source. They are updated as new results are published.
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