This is the NPU version of the repository https://github.com/NJUNLP/trans0 . The README provides users with a simple guide for setting up the NPU environment. For more detailed descriptions of the methods proposed in the paper, please refer to the original repository.

Cholesky decomposition reference implementation on Ascend NPU

Inference acceleration framework for breast cancer classification based on UNI and Huawei Ascend NPU, integrating structured pruning, Decoupled Knowledge Distillation (DKD), SVD, and INT8 quantization for edge-cloud deployment. 基于 UNI 病理大模型与华为昇腾 NPU 的乳腺癌分类推理加速方案，集成结构化剪枝、解耦知识蒸馏 (DKD)、SVD 低秩分解及 INT8 量化，实现端云协同部署。

MindX DL 组件部署/ 静态虚拟化、动态虚拟化 6.0.RC2