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90 lines
3.4 KiB
BibTeX
90 lines
3.4 KiB
BibTeX
@article{vaswani2017attention,
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title={Attention is all you need},
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author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
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journal={Advances in neural information processing systems},
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volume={30},
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year={2017}
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}
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@article{touvron2023llama,
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title={Llama: Open and efficient foundation language models},
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author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and others},
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journal={arXiv preprint arXiv:2302.13971},
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year={2023}
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}
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@article{hu2021lora,
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title={Lora: Low-rank adaptation of large language models},
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author={Hu, Edward J and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu},
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journal={arXiv preprint arXiv:2106.09685},
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year={2021}
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}
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@article{dettmers2023qlora,
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title={Qlora: Efficient finetuning of quantized llms},
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author={Dettmers, Tim and Pagnoni, Artidoro and Holtzman, Ari and Zettlemoyer, Luke},
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journal={arXiv preprint arXiv:2305.14314},
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year={2023}
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}
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@article{shazeer2019fast,
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title={Fast transformer decoding: One write-head is all you need},
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author={Shazeer, Noam},
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journal={arXiv preprint arXiv:1911.02150},
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year={2019}
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}
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@inproceedings{zhang2018improved,
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title={Improved variational autoencoders for text modeling using dilated convolutions},
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author={Zhang, Yizhe and Gan, Zhe and Fan, Kai and Chen, Zhi and Henao, Ricardo and Shen, Dinghan and Carin, Lawrence},
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booktitle={International conference on machine learning},
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pages={5655--5665},
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year={2018},
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organization={PMLR}
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}
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@article{team2024qwen,
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title={Qwen Technical Report},
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author={Qwen Team},
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journal={arXiv preprint arXiv:2407.10671},
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year={2024}
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}
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@article{gerganov2023llama,
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title={llama.cpp: Efficient LLM inference},
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author={Gerganov, Georgi},
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journal={GitHub repository},
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year={2023},
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url={https://github.com/ggerganov/llama.cpp}
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}
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@article{mlx2023apple,
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title={MLX: An efficient machine learning framework for Apple silicon},
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author={Apple Machine Learning Research},
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journal={GitHub repository},
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year={2023},
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url={https://github.com/ml-explore/mlx}
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}
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@article{brown2020language,
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title={Language models are few-shot learners},
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author={Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared D and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and others},
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journal={Advances in neural information processing systems},
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volume={33},
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pages={1877--1901},
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year={2020}
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}
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@article{kaplan2020scaling,
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title={Scaling laws for neural language models},
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author={Kaplan, Jared and McCandlish, Sam and Henighan, Tom and Brown, Tom B and Chess, Benjamin and Child, Rewon and Gray, Scott and Radford, Alec and Wu, Jeffrey and Amodei, Dario},
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journal={arXiv preprint arXiv:2001.08361},
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year={2020}
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}
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@article{hoffmann2022training,
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title={Training compute-optimal large language models},
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author={Hoffmann, Jordan and Borgeaud, Sebastian and Mensch, Arthur and Buchatskaya, Elena and Cai, Trevor and Rutherford, Eliza and Casas, Diego de Las and Hendricks, Lisa Anne and Welbl, Johannes and Clark, Aidan and others},
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journal={arXiv preprint arXiv:2203.15556},
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year={2022}
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} |