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## Description
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<!-- Provide a quick summary of what the model is/does. -->
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Models trained on 300B tokens, including dense FFN ones and low-rank FFN ones.
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## Citation
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If you find it useful, please consider citing the paper:
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```
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@article{wei2024building,
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title={Building on efficient foundations: Effective training of LLMs with structured feedforward layers},
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author={Wei, Xiuying and Moalla, Skander and Pascanu, Razvan and Gulcehre, Caglar},
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journal={Advances in Neural Information Processing Systems},
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volume={37},
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pages={4689--4717},
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year={2024}
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}
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@article{wei2024investigating,
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title={Investigating low-rank training in transformer language models: Efficiency and scaling analysis},
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author={Wei, Xiuying and Moalla, Skander and Pascanu, Razvan and Gulcehre, Caglar},
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journal={arXiv preprint arXiv:2407.09835},
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year={2024}
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}
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```
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