新闻
Pruning LLMs Like a Physicist: Block Removal as an Ising Optimization Problem
Hugging Face · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers reformulated LLM block removal as an Ising optimization problem, using physics-based methods to select which transformer blocks to delete for compression.
- 为何重要
- Engineers optimizing large language models for inference speed and memory should consider this when pursuing aggressive depth pruning beyond 30 percent compression.
- 注意
- The energy proxy is strong but imperfect; best results often come from excited states rather than ground states, requiring exploration of multiple candidates.
- llm
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