GPT-3GopherLaMDAGLaMMT-NLGPaLMChinchillaOPTUL2BLOOMFlan-T5ChatGPTBardClaudeGPT-4LLaMALlama 2AlpacaMPTXGenphiMistralYiGrokMay 2020Jan 2022Apr 2022Nov 2022Feb 2023Mar 2023Jul 2023Oct 2023Nov 20232023a). The ongoing research has also explored improving the agent (Xu et al., 2023d; Zeng et al.,
2023; Patil et al., 2023; Qin et al., 2023b), logical reasoning (Roziere et al., 2023; Luo et al., 2023a,c)
and long-context modeling (Tworkowski et al., 2023; Xiong et al., 2023; Xu et al., 2023b) capabilities
of Llama-based open-source LLMs. Besides, rather than developing LLMs based on Llama, many
efforts have been devoted to training powerful LLMs from scratch, e.g., MPT (Team, 2023), Falcon
(Almazrouei et al., 2023), XGen (Nijkamp et al., 2023), Phi (Gunasekar et al., 2023; Li et al., 2023e),
Baichuan (Yang et al., 2023a), Mistral (Jiang et al., 2023a), Grok (xAI, 2023) and Yi (01ai, 2023). We
believe that developing more powerful and efficient open-source LLMs to democratize the capabilities
ChatGPT’sOne-yearAnniversary-AreOpen-Source LargeLanguageModelsCatchingup