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 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.
These innovations can translate to real-world improvements in technology, infrastructure, and everyday tools.
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| Category | ⚙️ Engineering & Technology |
| Published | Jul 18, 2023 |
| Journal | arXiv (Cornell University) |
| Authors | Hugo Touvron, Louis Martin, Kevin H. Stone, Peter J. Albert, Amjad Almahairi |
| DOI | 10.48550/arxiv.2307.09288 |
| Citations | 2,622 |
| Source | OpenAlex |