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

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

X Title: GitHub - foresighty/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. - foresighty/DeepSpeed

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

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

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https://dev.azure.com/DeepSpeedMSFT/DeepSpeed/_build/latest?definitionId=1&branchName=master
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https://github.com/Microsoft/DeepSpeed/blob/master/LICENSE
DeepSpeedhttps://www.deepspeed.ai/
Turing-NLGhttps://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft
deepspeed.aihttps://www.deepspeed.ai/
https://github.com/foresighty/DeepSpeed#news
ZeRO-2 & DeepSpeed: Shattering Barriers of Deep Learning Speed & Scalehttps://www.microsoft.com/en-us/research/blog/zero-2-deepspeed-shattering-barriers-of-deep-learning-speed-scale/
An Order-of-Magnitude Larger and Faster Training with ZeRO-2https://www.deepspeed.ai/news/2020/05/18/zero-stage2.html
The Fastest and Most Efficient BERT Training through Optimized Transformer Kernelshttps://www.deepspeed.ai/news/2020/05/18/bert-record.html
Turing-NLG: A 17-billion-parameter language model by Microsofthttps://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/
ZeRO & DeepSpeed: New system optimizations enable training models with over 100 billion parametershttps://www.microsoft.com/en-us/research/blog/zero-deepspeed-new-system-optimizations-enable-training-models-with-over-100-billion-parameters/
https://github.com/foresighty/DeepSpeed#table-of-contents
Why DeepSpeed?https://github.com/foresighty/DeepSpeed#why-deepspeed
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https://github.com/foresighty/DeepSpeed#why-deepspeed
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feature overviewhttps://www.deepspeed.ai/features/
Distributed Training with Mixed Precisionhttps://www.deepspeed.ai/features/#distributed-training-with-mixed-precision
Model Parallelismhttps://www.deepspeed.ai/features/#model-parallelism
Memory and Bandwidth Optimizationshttps://www.deepspeed.ai/features/#memory-and-bandwidth-optimizations
Training Featureshttps://www.deepspeed.ai/features/#training-features
Training Optimizershttps://www.deepspeed.ai/features/#training-optimizers
Training Agnostic Checkpointinghttps://www.deepspeed.ai/features/#training-agnostic-checkpointing
Advanced Parameter Searchhttps://www.deepspeed.ai/features/#advanced-parameter-search
Simplified Data Loaderhttps://www.deepspeed.ai/features/#simplified-data-loader
Performance Analysis and Debugginghttps://www.deepspeed.ai/features/#performance-analysis-and-debugging
https://github.com/foresighty/DeepSpeed#further-reading
deepspeed.aihttps://www.deepspeed.ai/
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Getting Startedhttps://www.deepspeed.ai/getting-started/
DeepSpeed JSON Configurationhttps://www.deepspeed.ai/docs/config-json/
API Documentationhttps://deepspeed.readthedocs.io/en/latest/
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https://github.com/foresighty/DeepSpeed#contributing
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