2023-02-27 · preprint · Topic Modeling · en
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We introduce LLaMA, a collection of foundation 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.
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LLaMA: Open and Efficient Foundation Language Models is a preprint, focusing on Topic Modeling, published in 2023.
LLaMA: Open and Efficient Foundation Language Models has 4,523 citations in our record, placing it among the highly cited works we track.
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