LLM Compression by Block Removal with Constrained Binary Optimization
This paper forms the compression of large language models (LLMs) by optimally deleting transformer blocks (``block removal'') as a constrained binary optimization (CBO) problem that can be mapped to a physical system (Ising glass), whose energies are a strong proxy for downstream model performance.
David Jansen, Roman Rausch, Ali Hashemi et al.
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