Paper · arXiv 2401.02385
TinyLlama: An Open-Source Small Language Model
Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, Wei Lu
TinyLlama, a compact 1.1B language model, leverages FlashAttention to achieve high performance in downstream tasks with enhanced computational efficiency.
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), 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.