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The Unreasonable Ineffectiveness of the Deeper Layers
Study explores layer pruning in pretrained LLMs, finding minimal performance drop until half of layers removed. Optimal block identified for pruning, followed by finetuning with PEFT methods for efficiency and improved inference.
https://arxiv.org/abs//2403.17887
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
Study explores layer pruning in pretrained LLMs, finding minimal performance drop until half of layers removed. Optimal block identified for pruning, followed by finetuning with PEFT methods for efficiency and improved inference.
https://arxiv.org/abs//2403.17887
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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