LLM compression method jointly optimizes architecture and quantization

Arxiv CS.LG (machine learning)

The paper proposes a method to compress large language models by simultaneously optimizing architectural choices and quantization parameters, reducing memory and computational requirements. This approach addresses deployment challenges without requiring extensive GPU resources for training small models from scratch.

llmcompression

Arxiv CS.LG (machine learning)·Hoang-Loc LaTruong-Thanh LeAmir TaherkordiPhuong Hoai Ha

7 days ago