--- license: apache-2.0 base_model: - Qwen/Qwen3-Coder-30B-A3B-Instruct library_name: transformers --- # Qwen3-Coder-30B-A3B-Instruct-ScatterMoE Re-packed weights of [Qwen/Qwen3-Coder-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) using [Charles Goddard](https://huggingface.co/chargoddard)'s remote code implementation of [scattermoe](https://github.com/shawntan/scattermoe), including scripts to convert to and from standard `Qwen3MoeForCausalLM`. Thank you to [intervitens](https://huggingface.co/intervitens) for assistance with memory-efficient conversion scripts! This is intended to be used as a drop-in replacement for efficient training using any `transformers`-based training repository. Optional monkeypatches included for [Liger Kernel](https://github.com/linkedin/Liger-Kernel) and [Cut Cross-Entropy](https://github.com/apple/ml-cross-entropy). Simply rename the relevant modeling file to `modeling_qwen3_shared_moe.py`. ## Citations ``` @misc{qwen3technicalreport, title={Qwen3 Technical Report}, author={Qwen Team}, year={2025}, eprint={2505.09388}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2505.09388}, } @misc{tan2024scatteredmixtureofexpertsimplementation, title={Scattered Mixture-of-Experts Implementation}, author={Shawn Tan and Yikang Shen and Rameswar Panda and Aaron Courville}, year={2024}, eprint={2403.08245}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={https://arxiv.org/abs/2403.08245}, } @misc{hsu2025ligerkernelefficienttriton, title={Liger Kernel: Efficient Triton Kernels for LLM Training}, author={Pin-Lun Hsu and Yun Dai and Vignesh Kothapalli and Qingquan Song and Shao Tang and Siyu Zhu and Steven Shimizu and Shivam Sahni and Haowen Ning and Yanning Chen}, year={2025}, eprint={2410.10989}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={https://arxiv.org/abs/2410.10989}, } @misc{wijmans2025cutlosseslargevocabularylanguage, title={Cut Your Losses in Large-Vocabulary Language Models}, author={Erik Wijmans and Brody Huval and Alexander Hertzberg and Vladlen Koltun and Philipp Krähenbühl}, year={2025}, eprint={2411.09009}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={https://arxiv.org/abs/2411.09009}, } ```