SEMIKONG is an open-source, industry-specific large language model (LLM) tailored to the semiconductor domain. It aims to address the unique challenges faced by the semiconductor industry, such as the physics and chemistry of semiconductor devices and processes, by incorporating domain-specific knowledge into the model.
- First industry-specific LLM for the semiconductor domain
- Trained on a comprehensive semiconductor-related text corpus
- Novel pre-training approach leveraging domain-specific knowledge
- Superior performance compared to general-purpose LLMs on industry-relevant benchmarks
- Serves as a valuable foundation for companies to build proprietary models tailored to their needs
This project is the result of a collaborative effort involving multiple companies and individuals:
- Tokyo Electron: Atsushi Suzuki, Daisuke Oku
- Aitomatic: Daniel Guttierez, Vinh Luong, Christopher Nguyen.
- FPT Software AIC: Huy Vo, Thang Nguyen, Lan Nguyen
- AI Alliance members and researchers
We would like to express our gratitude to the AI Alliance (https://thealliance.ai) for providing the impetus, resources, and platform for this work, and for collaboration in open science. We also extend our thanks to the member organizations of the AI Alliance, their researchers and engineers for their valuable contributions to this study, including:
- Noritaka Yokomori (Tokyo Electron)
- Anthony Annunziata (IBM Research)
- Sean Hughes (ServiceNow)
- Phong Nguyen (FPT Software, AI Center)
Their expertise, insights, and collaborative spirit have been instrumental in advancing our research.
To get started with SemiKong, please refer to the installation guide and usage instructions.
This project is licensed under the Apache 2.0 License.
If you use SemiKong in your research or development work, please cite our paper:
@article{semikong2024,
title={SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language Model},
author={Christopher Nguyen et al.},
journal={arXiv preprint arXiv:2024.xxxxx},
year={2024}
}For questions, suggestions, or collaborations, please contact the SemiKong team at [email protected]