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SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Shafipour, Rasoul, Harrison, David, Horton, Maxwell, Marker, Jeffrey, Bedayat, Houman, Mehta, Sachin, Rastegari, Mohammad, Najibi, Mahyar, Naderiparizi, Saman
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
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