Pruning Large Models
Recent findings reveal that many layers in large language models exhibit redundancy, suggesting that some contribute minimally to functionality. Researchers introduced a metric called block influence to assess layer significance, leading to a proposed method for model pruning through layer removal. This approach could make inference cheaper while enhancing efficiency, complementing existing methods like quantization.In this clip
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Last Week in AI #159 - Inflection-2.5, Devin, OpenAI board update, SIMA, EU AI Act passed
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