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We introduce Mini-Sequence Transformer (MsT), a simple and effective methodology for highly efficient and accurate LLM training with extremely long sequences.
The cross-entropy method for combinatorial and continuous optimization
Reuven Rubinstein · 1999
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Training deep nets with sublinear memory cost
Tianqi Chen, Bing Xu, Chiyuan Zhang, and Carlos Guestrin · 2016
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Accumulated gradient normalization
Joeri R Hermans, Gerasimos Spanakis, and Rico Möckel · 2017
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Mini-batch gradient descent: Faster convergence under data sparsity
Sarit Khirirat, Hamid Reza Feyzmahdavian, and Mikael Johansson · 2017
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Searching for activation functions
Prajit Ramachandran, Barret Zoph, and Quoc V Le · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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gradient-checkpointing
OpenAI · 2018
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Scaling neural machine translation
Myle Ott, Sergey Edunov, David Grangier, and Michael Auli · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern · 2018
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Generating long sequences with sparse transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
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Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov · 2019
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Gpipe: Efficient training of giant neural networks using pipeline parallelism
Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V Le, Yonghui Wu, et al · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Fast transformer decoding: One write-head is all you need
Noam Shazeer · 2019
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Megatron-lm: Training multi-billion parameter language models using model parallelism
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper, and Bryan Catanzaro · 2019
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al · 2020
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Booksum: A collection of datasets for long-form narrative summarization
Wojciech Kryściński, Nazneen Rajani, Divyansh Agarwal, Caiming Xiong, and Dragomir Radev · 2021
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Sequence parallelism: Long sequence training from system perspective
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
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Reducing activation recomputation in large transformer models
Vijay Anand Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee, Michael Andersch, Mohammad Shoeybi, and Bryan Catanzaro · 2023
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Ring attention with blockwise transformers for near-infinite context
Hao Liu, Matei Zaharia, and Pieter Abbeel · 2023
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Large language models are few-shot health learners
Xin Liu, Daniel McDuff, Geza Kovacs, Isaac Galatzer-Levy, Jacob Sunshine, Jiening Zhan, Ming-Zher Poh, Shun Liao, Paolo Di Achille, and Shwetak Patel · 2023
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Adalomo: Low-memory optimization with adaptive learning rate
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Shenggui Li, Fuzhao Xue, Chaitanya Baranwal, Yongbin Li, and Yang You · 2021
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Edgar-corpus: Billions of tokens make the world go round
Lefteris Loukas, Manos Fergadiotis, Ion Androutsopoulos, and Prodromos Malakasiotis · 2021
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Efficient large-scale language model training on gpu clusters using megatron-lm
Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, et al · 2021
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Self-attention does not need o (n2̂) memory
Markus N Rabe and Charles Staats · 2021
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Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, and Yuxiong He · 2021
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Efficient content-based sparse attention with routing transformers
Aurko Roy, Mohammad Saffar, Ashish Vaswani, and David Grangier · 2021
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Hugging face
Shashank Mohan Jain · 2022
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Kai Lv, Hang Yan, Qipeng Guo, Haijun Lv, and Xipeng Qiu · 2023
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Efficient cross entropy
Mohammad Malek et al · 2023
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Climax: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, and Aditya Grover · 2023
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S-lora: Serving thousands of concurrent lora adapters
Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Efficient streaming language models with attention sinks
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Effective long-context scaling of foundation models
Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, et al · 2023
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Pytorch fsdp: experiences on scaling fully sharded data parallel
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Genslms: Genome-scale language models reveal sars-cov-2 evolutionary dynamics
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Phi-3 technical report: A highly capable language model locally on your phone
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optimizer step in backward tutorial
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Qlora: Efficient finetuning of quantized llms
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Transformerfam: Feedback attention is working memory
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
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Gemma: Open models based on gemini research and technology
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