MinPLM-Qwen-200M
MiniPLM-Qwen-200M is a 200M model with Qwen achitecture pre-trained from scratch on the Pile using the MiniPLM knowledge distillation framework with the offcial Qwen1.5-1.8B as the teacher model.
We also open-source the pre-training corpus refined by Difference Sampling in MiniPLM for reproducibility.
Evaluation
MiniPLM models achieves better performance given the same computation and scales well across model sizes:
Baseline Models
Citation
@article{miniplm,
title={MiniPLM: Knowledge Distillation for Pre-Training Language Models},
author={Yuxian Gu and Hao Zhou and Fandong Meng and Jie Zhou and Minlie Huang},
journal={arXiv preprint arXiv:2410.17215},
year={2024}
}