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Computer Science > Computation and Language

arXiv:2401.02385 (cs)
[Submitted on 4 Jan 2024]

Title:TinyLlama: An Open-Source Small Language Model

Authors:Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, Wei Lu
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Language Model, by Peiyuan Zhang and 3 other authors
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    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 this
    https URL.

Comments: Technical Report
Subjects: Computation and Language (cs.CL); Artificial Intelligence
          (cs.AI)
Cite as:  arXiv:2401.02385 [cs.CL]
          (or arXiv:2401.02385v1 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2401.02385
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Guangtao Zeng [view email]
[v1] Thu, 4 Jan 2024 17:54:59 UTC (1,783 KB)
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