NLP
LLaMA: Open and Efficient Foundation Language Models
February 24, 2023
Abstract
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.
AUTHORS
Written by
Edouard Grave
Faisal Azhar
Armand Joulin
Aurelien Rodriguez
Eric Hambro
Gautier Izacard
Guillaume Lample
Marie-Anne Lachaux
Naman Goyal
Thibaut Lavril
Timothee Lacroix
Xavier Martinet
Publisher
ArXiV
Research Topics
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