Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework

no code implementations • 17 Mar 2024 • Kaiyan Chang, Kun Wang, Nan Yang, Ying Wang, Dantong Jin, Wenlong Zhu, Zhirong Chen, Cangyuan Li, Hao Yan, Yunhao Zhou, Zhuoliang Zhao, Yuan Cheng, Yudong Pan, Yiqi Liu, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li

Our 13B model (ChipGPT-FT) has a pass rate improvement compared with GPT-3. 5 in Verilog generation and outperforms in EDA script (i. e., SiliconCompiler) generation with only 200 EDA script data.

Data Augmentation GPT-3.5

Can We Trust Race Prediction?

1 code implementation • 17 Jul 2023 • Cangyuan Li

In the absence of sensitive race and ethnicity data, researchers, regulators, and firms alike turn to proxies.