BWhat changed
Developed a family of 7B–65B-parameter foundation language models trained on publicly available datasets and reported competitive language-task performance relative to much larger contemporary models.
Scientific scope
Developed a family of 7B–65B-parameter foundation language models trained on publicly available datasets and reported competitive language-task performance relative to much larger contemporary models. Scope limitation: The exact 2023 LLaMA paper is distinct from later Llama 2/3 releases. Its reported comparisons are benchmark- and setup-specific; this record makes no claim about unrestricted public access or all downstream safety properties.
Evidence
The retained primary-source abstract, bibliographic record and stated review scope support this provisional assessment. No independent experimental replication by WRS is claimed. The exact 2023 LLaMA paper is distinct from later Llama 2/3 releases. Its reported comparisons are benchmark- and setup-specific; this record makes no claim about unrestricted public access or all downstream safety properties.
Contributors
- The named authors listed in the linked research record · SCIENCE: Complete source byline retained in the research record; human research direction, method development and evaluation. Individual labor shares are not measured.
- LLaMA: Open and Efficient Foundation Language Models
- LLaMA: Open and Efficient Foundation Language Models — AI at Meta
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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