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YaRN (Llama 2 13B)

Training compute
1.9×10²⁰ FLOP
Parameters
13B
Published
Nov 1, 2023

YaRN (Llama 2 13B) is an AI model developed by Nous Research, EleutherAI and University of Geneva (United States and Switzerland), first published in November 2023. It works in the language domain, on tasks such as language modeling/generation and question answering.

Training it took an estimated 1.9×10²⁰ FLOP of compute (estimation method: operation counting). The model has 13,000,000,000 parameters. It was trained on roughly 2.5B datapoints.

Access: Open weights (restricted use). Its weights are openly available. It is built on top of Llama 2-13B. Epoch AI rates the confidence of this record as confident.

Full record
Organization
Nous Research, EleutherAI, University of Geneva
Country of organization
United States, Switzerland
Domain
Language
Task
Language modeling/generation, Question answering
Training compute
1.9×10²⁰ FLOP
Compute estimation method
Operation counting
Parameters
13,000,000,000
Dataset size
2.5B
Model accessibility
Open weights (restricted use)
Open weights
Yes
Base model
Llama 2-13B
Epoch confidence
Confident
More from Nous Research,EleutherAI,University of Geneva
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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