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Title: GitHub - codeaudit/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. · GitHub

Open Graph Title: GitHub - codeaudit/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

X Title: GitHub - codeaudit/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Description: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. - codeaudit/DeepSpeed

Open Graph Description: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. - codeaudit/DeepSpeed

X Description: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. - codeaudit/DeepSpeed

Mail addresses
opencode@microsoft.com

Opengraph URL: https://github.com/codeaudit/DeepSpeed

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	https://dev.azure.com/DeepSpeedMSFT/DeepSpeed/_build/latest?definitionId=1&branchName=master
	https://github.com/Microsoft/DeepSpeed/blob/master/LICENSE
Turing-NLG	https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft
	https://github.com/codeaudit/DeepSpeed#table-of-contents
Why DeepSpeed?	https://github.com/codeaudit/DeepSpeed#why-deepspeed
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	https://github.com/codeaudit/DeepSpeed#why-deepspeed
	https://github.com/codeaudit/DeepSpeed#distributed-effective-and-efficient-training-with-ease
PyTorch	https://pytorch.org/
	https://github.com/codeaudit/DeepSpeed#speed
GPT tutorial	https://github.com/codeaudit/DeepSpeed/blob/master/docs/tutorials/MegatronGPT2Tutorial.md
	https://github.com/codeaudit/DeepSpeed#memory-efficiency
paper	https://arxiv.org/abs/1910.02054
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	https://github.com/codeaudit/DeepSpeed#scalability
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	https://github.com/codeaudit/DeepSpeed/blob/master/docs/figures/DeepSpeed-vs-Megatron.png
	https://github.com/codeaudit/DeepSpeed#fast-convergence-for-effectiveness
LAMB	https://arxiv.org/abs/1904.00962
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	https://github.com/codeaudit/DeepSpeed#good-usability
	https://github.com/codeaudit/DeepSpeed#features
feature overview	https://github.com/codeaudit/DeepSpeed/blob/master/docs/features.md
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	https://github.com/codeaudit/DeepSpeed#getting-started
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install.sh	https://github.com/codeaudit/DeepSpeed/blob/master/install.sh
	https://github.com/codeaudit/DeepSpeed#writing-deepspeed-models
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	https://github.com/codeaudit/DeepSpeed#training
	https://github.com/codeaudit/DeepSpeed#model-checkpointing
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	https://github.com/codeaudit/DeepSpeed#launching-deepspeed-training
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	https://github.com/codeaudit/DeepSpeed#contributing
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https://cla.opensource.microsoft.com	https://cla.opensource.microsoft.com
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Microsoft Open Source Code of Conduct	https://opensource.microsoft.com/codeofconduct/
Code of Conduct FAQ	https://opensource.microsoft.com/codeofconduct/faq/
	https://github.com/codeaudit/DeepSpeed#publications
ArXiv:1910.02054	https://arxiv.org/abs/1910.02054
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