  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.
