Llama 2: Open Foundation and Fine-Tuned Chat Models
Authors: name: Hugo Touvron, name: Louis Martin, name: Kevin Stone, name: Peter Albert, name: Amjad Almahairi, name: Yasmine Babaei, name: Nikolay Bashlykov, name: Soumya Batra, name: Prajjwal Bhargava, name: Shruti Bhosale, name: Dan Bikel, name: Lukas Blecher, name: Cristian Canton Ferrer, name: Moya Chen, name: Guillem Cucurull, name: David Esiobu, name: Jude Fernandes, name: Jeremy Fu, name: Wenyin Fu, name: Brian Fuller, name: Cynthia Gao, name: Vedanuj Goswami, name: Naman Goyal, name: Anthony Hartshorn, name: Saghar Hosseini, name: Rui Hou, name: Hakan Inan, name: Marcin Kardas, name: Viktor Kerkez, name: Madian Khabsa, name: Isabel Kloumann, name: Artem Korenev, name: Punit Singh Koura, name: Marie-Anne Lachaux, name: Thibaut Lavril, name: Jenya Lee, name: Diana Liskovich, name: Yinghai Lu, name: Yuning Mao, name: Xavier Martinet, name: Todor Mihaylov, name: Pushkar Mishra, name: Igor Molybog, name: Yixin Nie, name: Andrew Poulton, name: Jeremy Reizenstein, name: Rashi Rungta, name: Kalyan Saladi, name: Alan Schelten, name: Ruan Silva, name: Eric Michael Smith, name: Ranjan Subramanian, name: Xiaoqing Ellen Tan, name: Binh Tang, name: Ross Taylor, name: Adina Williams, name: Jian Xiang Kuan, name: Puxin Xu, name: Zheng Yan, name: Iliyan Zarov, name: Yuchen Zhang, name: Angela Fan, name: Melanie Kambadur, name: Sharan Narang, name: Aurelien Rodriguez, name: Robert Stojnic, name: Sergey Edunov, name: Thomas Scialom

In this work, we develop and release Llama 2, a collection of pretrained and
fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70
billion parameters. Our fine-tuned LLMs, called Llama 2-Chat, are optimized for
dialogue use cases. Our models outperform open-source chat models on most
benchmarks we tested, and based on our human evaluations for helpfulness and
safety, may be a suitable substitute for closed-source models. We provide a
detailed description of our approach to fine-tuning and safety improvements of
Llama 2-Chat in order to enable the community to build on our work and
contribute to the responsible development of LLMs.