GPT-J-6B

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. XGen-7B Technical Report ↗

   Nijkamp, Erik, Xie, Tian, Hayashi, Hiroaki, Pang, Bo, Xia, Congying, Xing, Chen et al. · 2023

   All 25 authors

   Nijkamp, Erik, Xie, Tian, Hayashi, Hiroaki, Pang, Bo, Xia, Congying, Xing, Chen, Vig, Jesse, Yavuz, Semih, Laban, Philippe, Krause, Ben, Purushwalkam, Senthil, Niu, Tong, Kryściński, Wojciech, Murakhovs'ka, Lidiya, Choubey, Prafulla Kumar, Fabbri, Alex, Liu, Ye, Meng, Rui, Tu, Lifu, Bhat, Meghana, Wu, Chien-Sheng, Savarese, Silvio, Zhou, Yingbo, Joty, Shafiq, Xiong, Caiming

2. Holistic Evaluation of Language Models (HELM) ↗

   Stanford Center for Research on Foundation Models

3. Holistic Evaluation of Language Models (HELM) ↗

   Stanford Center for Research on Foundation Models

4. Holistic Evaluation of Language Models (HELM) ↗

   Stanford Center for Research on Foundation Models

5. Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation — published result table ↗

   Liu, Jiawei, Xia, Chunqiu Steven, Wang, Yuyao, Zhang, Lingming · 2023

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

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