GPT-3 175B

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

1. GLaM: Efficient Scaling of Language Models with Mixture-of-Experts ↗

   Du, Nan, Huang, Yanping, Dai, Andrew M., Tong, Simon, Lepikhin, Dmitry, Xu, Yuanzhong et al. · 2021

   All 27 authors

   Du, Nan, Huang, Yanping, Dai, Andrew M., Tong, Simon, Lepikhin, Dmitry, Xu, Yuanzhong, Krikun, Maxim, Zhou, Yanqi, Yu, Adams Wei, Firat, Orhan, Zoph, Barret, Fedus, Liam, Bosma, Maarten, Zhou, Zongwei, Wang, Tao, Wang, Yu Emma, Webster, Kellie, Pellat, Marie, Robinson, Kevin, Meier-Hellstern, Kathleen, Duke, Toju, Dixon, Lucas, Zhang, Kun, Le, Quoc V, Wu, Yonghui, Chen, Zhifeng, Cui, Claire

2. LLaMA: Open and Efficient Foundation Language Models ↗

   Touvron, Hugo, Lavril, Thibaut, Izacard, Gautier, Martinet, Xavier, Lachaux, Marie-Anne, Lacroix, Timothée et al. · 2023

   All 14 authors

   Touvron, Hugo, Lavril, Thibaut, Izacard, Gautier, Martinet, Xavier, Lachaux, Marie-Anne, Lacroix, Timothée, Rozière, Baptiste, Goyal, Naman, Hambro, Eric, Azhar, Faisal, Rodriguez, Aurelien, Joulin, Armand, Grave, Edouard, Lample, Guillaume

3. BizBench: A Quantitative Reasoning Benchmark for Business and Finance — published result table ↗

   Rik Koncel-Kedziorski, Michael Krumdick, Viet Lai, Varshini Reddy, Charles Lovering, Chris Tanner · 2023

4. TruthfulQA: Measuring How Models Mimic Human Falsehoods — published result table ↗

   Lin, Stephanie, Hilton, Jacob, Evans, Owain · 2021