Computational Bottlenecks of Training Small-scale Large Language Models
from Arxiv Papers Hosted by Igor Melnyk
This study investigates the training behavior and computational requirements of Small-scale Large Language Models (SLMs), focusing on hyperparameters and configurations to enhance efficiency and support low-resource AI research. https://arxiv.org/abs//2410.19456 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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This episode was published on October 28, 2024.
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