#python #billion_parameters #data_parallelism #deep_learning #gpu #machine_learning #model_parallelism #pytorch

https://github.com/microsoft/DeepSpeed

#python #data_parallelism #deep_learning #distributed_training #hpc #large_scale #model_parallelism #pipeline_parallelism

https://github.com/hpcaitech/ColossalAI

#python #billion_parameters #compression #data_parallelism #deep_learning #gpu #inference #machine_learning #mixture_of_experts #model_parallelism #pipeline_parallelism #pytorch #trillion_parameters #zero

DeepSpeed is a powerful tool for training and using large artificial intelligence models quickly and efficiently. It allows you to train models with billions or even trillions of parameters, which is much faster and cheaper than other methods. With DeepSpeed, you can achieve significant speedups, reduce costs, and improve the performance of your models. For example, it can train ChatGPT-like models 15 times faster than current state-of-the-art systems. This makes it easier to work with large language models without needing massive resources, making AI more accessible and efficient for everyone.

https://github.com/microsoft/DeepSpeed

#python #ai #big_model #data_parallelism #deep_learning #distributed_computing #foundation_models #heterogeneous_training #hpc #inference #large_scale #model_parallelism #pipeline_parallelism

Colossal-AI is a powerful tool that helps make large AI models faster, cheaper, and easier to use. It uses special techniques like parallelism to speed up training on big models without needing expensive hardware. This means users can train complex AI models even on regular computers or laptops, saving time and money. Colossal-AI also supports various applications across industries like medicine, video generation, and chatbots, making it very versatile for developers.

https://github.com/hpcaitech/ColossalAI