---
license: mit
datasets:
- tiiuae/falcon-refinedweb
language:
- en
metrics:
- perplexity
- accuracy
---
## Description

<!-- Provide a quick summary of what the model is/does. -->

Models trained on 300B tokens, including dense FFN ones and low-rank FFN ones.



## Citation 

If you find it useful, please consider citing the paper:

```
@article{wei2024building,
  title={Building on efficient foundations: Effective training of LLMs with structured feedforward layers},
  author={Wei, Xiuying and Moalla, Skander and Pascanu, Razvan and Gulcehre, Caglar},
  journal={Advances in Neural Information Processing Systems},
  volume={37},
  pages={4689--4717},
  year={2024}
}

@article{wei2024investigating,
  title={Investigating low-rank training in transformer language models: Efficiency and scaling analysis},
  author={Wei, Xiuying and Moalla, Skander and Pascanu, Razvan and Gulcehre, Caglar},
  journal={arXiv preprint arXiv:2407.09835},
  year={2024}
}
```