English

TinyLlama: An Open-Source Small Language Model

Computation and Language 2024-06-05 v2 Artificial Intelligence

Abstract

We present TinyLlama, a compact 1.1B language model pretrained on around 1 trillion tokens for approximately 3 epochs. Building on the architecture and tokenizer of Llama 2, TinyLlama leverages various advances contributed by the open-source community (e.g., FlashAttention and Lit-GPT), achieving better computational efficiency. Despite its relatively small size, TinyLlama demonstrates remarkable performance in a series of downstream tasks. It significantly outperforms existing open-source language models with comparable sizes. Our model checkpoints and code are publicly available on GitHub at https://github.com/jzhang38/TinyLlama.

Keywords

Cite

@article{arxiv.2401.02385,
  title  = {TinyLlama: An Open-Source Small Language Model},
  author = {Peiyuan Zhang and Guangtao Zeng and Tianduo Wang and Wei Lu},
  journal= {arXiv preprint arXiv:2401.02385},
  year   = {2024}
}

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Technical Report

R2 v1 2026-06-28T14:08:51.969Z