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pro vyhledávání: '"Oh, JiHun"'
Prior research works have evaluated quantized LLMs using limited metrics such as perplexity or a few basic knowledge tasks and old datasets. Additionally, recent large-scale models such as Llama 3.1 with up to 405B have not been thoroughly examined.
Externí odkaz:
http://arxiv.org/abs/2409.11055
Publikováno v:
In Nano Energy November 2024 130
Autor:
Choi, Hyeonuk, Ha, Min Gwan, Suh, Jungwon, Lim, Chulwan, Kim, Beomil, Wang, Sun Eon, Lee, Jang Yong, Oh, Hyung-Suk, Oh, Jihun
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 October 2024 355
This paper aims to provide a selective survey about knowledge distillation(KD) framework for researchers and practitioners to take advantage of it for developing new optimized models in the deep neural network field. To this end, we give a brief over
Externí odkaz:
http://arxiv.org/abs/2011.14554
Post-training, layer-wise quantization is preferable because it is free from retraining and is hardware-friendly. Nevertheless, accuracy degradation has occurred when a neural network model has a big difference of per-out-channel weight ranges. In pa
Externí odkaz:
http://arxiv.org/abs/2008.05767
Akademický článek
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Autor:
Lee, Youngki, Kang, Subin, Thuy, Le Thi, Son, Mincheol, Park, Jae Young, Ahn, Sung Bin, Kang, Minji, Oh, Jihun, Choi, Joon Sig, Lee, Minhyung
Publikováno v:
In Asian Journal of Pharmaceutical Sciences October 2024
Autor:
Kim, Jaehoon, Ha, Tae Hyeon, Kim, Junehyeok, Jeong, Gyoung Hwa, Kim, Sang Ouk, Chung, Wonsuk, Roh, Kosan, Lee, Jay H., Oh, Jihun
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 December 2023 339
Autor:
Zhang, Wenjun, Choi, Jae Won, Kim, Sooyeon, Le, Thao Thi, Nandy, Subhajit, Hwang, Chang-Kyu, Paek, Sae Yane, Byeon, Ayeong, Chae, Keun Hwa, Lee, Seung Yong, Kim, Sang Hoon, Song, Hakhyeon, Kim, Jaehoon, Oh, Jihun, Lee, Jae W., Han, Sang Soo, Kim, Jong Min
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 August 2023 331