TinyLlama: An Open-Source Small Language Model
Zhang, Peiyuan, Zeng, Guangtao, Wang, Tianduo, Lu, Wei
–arXiv.org Artificial Intelligence
Building on the architecture and tokenizer of Llama 2 (Touvron et al., 2023b), TinyLlama leverages various advances contributed by the open-source community (e.g., FlashAttention (Dao, 2023)), 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.
arXiv.org Artificial Intelligence
Jan-4-2024
- Country:
- Asia > Singapore (0.05)
- North America > United States
- California > Los Angeles County > Long Beach (0.04)
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- Research Report (1.00)
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