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[short] EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
EAGLE is a lossless acceleration framework for Large Language Models, achieving faster decoding without fine-tuning and maintaining the same text distribution.
https://arxiv.org/abs//2401.15077
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
EAGLE is a lossless acceleration framework for Large Language Models, achieving faster decoding without fine-tuning and maintaining the same text distribution.
https://arxiv.org/abs//2401.15077
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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