AI models
YaRN (Llama 2 70B)
Training compute
10²¹ FLOP
Parameters
70B
Published
Nov 1, 2023
YaRN (Llama 2 70B) 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 10²¹ FLOP of compute (estimation method: operation counting). The model has 70,000,000,000 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 2-70B. Epoch AI rates the confidence of this record as likely.
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
- 10²¹ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 70,000,000,000
- Dataset size
- 2.5B
- Model accessibility
- Open weights (restricted use)
- Open weights
- Yes
- Base model
- Llama 2-70B
- Epoch confidence
- Likely
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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