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  1. CASE-Lab-UMD/LLM-Drop CASE-Lab-UMD/LLM-Drop Public

    The official implementation of the paper "What Matters in Transformers? Not All Attention is Needed".

    Python 171 20

  2. CASE-Lab-UMD/Unified-MoE-Compression CASE-Lab-UMD/Unified-MoE-Compression Public

    The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".

    Python 68 5

  3. CASE-Lab-UMD/Router-Tuning-Mixture-of-Depths CASE-Lab-UMD/Router-Tuning-Mixture-of-Depths Public

    The open-source Mixture of Depths code and the official implementation of the paper "Router-Tuning: A Simple and Effective Approach for Enabling Dynamic Depth in Transformers."

    Python 11 2

  4. MEO MEO Public

    The source code of "Merging Experts into One: Improving Computational Efficiency of Mixture of Experts (EMNLP 2023)":

    Python 38 2

  5. SparseAdapter SparseAdapter Public

    Source code of EMNLP 2022 Findings paper "SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters"

    Python 18

  6. PAD-Net PAD-Net Public

    Source code of ACL 2023 Main Conference Paper "PAD-Net: An Efficient Framework for Dynamic Networks".

    Python 9

0