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DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
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Latest capture 2026-07-04 03:08
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Scanned 2026-07-04 03:08
setup.cfg
python ecosystem,
0 dependencies
setup.py
python ecosystem,
0 dependencies
docs/Gemfile
ruby ecosystem,
10 dependencies
requirements/requirements-1bit-mpi.txt
python ecosystem,
1 dependency
requirements/requirements-autotuning-ml.txt
python ecosystem,
3 dependencies
requirements/requirements-autotuning.txt
python ecosystem,
1 dependency
requirements/requirements-cpu.txt
python ecosystem,
1 dependency
requirements/requirements-dev.txt
python ecosystem,
21 dependencies
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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
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A Next-Generation Training Engine Built for Ultra-Large MoE Models
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
