Llama 2: Open Foundation and Fine-Tuned Chat Models

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Resource type
Preprint
Authors/contributors
Title
Llama 2: Open Foundation and Fine-Tuned Chat Models
Abstract
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.
Repository
arXiv
Archive ID
arXiv:2307.09288
Date
2023-07-19
DOI
10.48550/arXiv.2307.09288
URL
http://arxiv.org/abs/2307.09288
Accessed
24/02/2024, 17:41
Short Title
Llama 2
Library Catalogue
arXiv.org
Extra
arXiv:2307.09288 [cs]
Citation
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Ferrer, C. C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., … Scialom, T. (2023). Llama 2: Open Foundation and Fine-Tuned Chat Models (arXiv:2307.09288). arXiv. https://doi.org/10.48550/arXiv.2307.09288
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Link to this record
https://docs.opendeved.net/lib/JXSFG6IR