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sparse-communication

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gelassal / MEFT-LLM-Sparse-Adapters

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Implementation and evaluation of memory-efficient adapter-based fine-tuning for llm's. This project compares a standard GPU-based adapter approach with a sparse CPU-based adapter (MEFT), analyzing training speed and GPU memory usage across different adapter ranks. Includes custom adapter injection into GPT-2, Top-K sparse activation, and results.

machine-learning deep-learning transformers pytorch top-k adapters peft memory-optimization llm sparse-communication
  • Updated May 3, 2026
  • Python

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