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Public本项目探索并实现超越传统 Transformer 架构的高效序列建模方法,重点关注状态空间模型(SSM)Mamba 和线性注意力机制等新型架构。项目基于Pytorch框架,从零设计实现了一套完整的模型训练、评估、记录和可视化方案,并完成 GLUE Benchmark 和 LRA 的适配工作。
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Large-scale datasets and benchmarks for training, evaluating, and testing models to measure
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本项目探索并实现超越传统 Transformer 架构的高效序列建模方法,重点关注状态空间模型(SSM)Mamba 和线性注意力机制等新型架构。项目基于Pytorch框架,从零设计实现了一套完整的模型训练、评估、记录和可视化方案,并完成 GLUE Benchmark 和 LRA 的适配工作。