February 24, 2023
We introduce LLaMA, a collection of founda- tion language models ranging from 7B to 65B parameters. We train our models on trillions of tokens, and show that it is possible to train state-of-the-art models using publicly available datasets exclusively, without resorting to proprietary and inaccessible datasets. In particular, LLaMA-13B outperforms GPT-3 (175B) on most benchmarks, and LLaMA-65B is competitive with the best models, Chinchilla- 70B and PaLM-540B. We release all our models to the research community.
Written by
Faisal Azhar
Armand Joulin
Aurelien Rodriguez
Eric Hambro
Gautier Izacard
Guillaume Lample
Marie-Anne Lachaux
Naman Goyal
Thibaut Lavril
Timothee Lacroix
Xavier Martinet
Edouard Grave
Publisher
ArXiV
Research Topics
July 23, 2024
Llama team
July 23, 2024
June 25, 2024
Elena Voita, Javier Ferrando Monsonis, Christoforos Nalmpantis
June 25, 2024
June 25, 2024
Min-Jae Hwang, Ilia Kulikov, Benjamin Peloquin, Hongyu Gong, Peng-Jen Chen, Ann Lee
June 25, 2024
June 14, 2024
Sheng-Chieh Lin, Akari Asai, Minghan Li, Barlas Oguz, Jimmy Lin, Scott Yih, Xilun Chen
June 14, 2024
Product experiences
Foundational models
Product experiences
Latest news
Foundational models