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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.
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Hugo Touvron
Louis Martin
Kevin H. Stone
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Touvron et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69dc1db0ce788f95bfb64f98 — DOI: https://doi.org/10.48550/arxiv.2307.09288