most citedFP8-BERT: Post-Training Quantization for Transformer

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2023★ 2 cited

FP8-BERT: Post-Training Quantization for Transformer

Jianwei Li, Tianchi Zhang, Ian En-Hsu Yen +1

Transformer-based models, such as BERT, have been widely applied in a wide range of natural language processing tasks. However, one inevitable side effect is that they require mass…

cs.CV2022★ 1 cited

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

Shengkun Tang, Yaqing Wang, Zhenglun Kong +6

Large-scale Transformer models bring significant improvements for various downstream vision language tasks with a unified architecture. The performance improvements come with incre…