{"library":"deepspeed","type":"library","category":null,"description":"DeepSpeed is a deep learning optimization library for PyTorch, developed by Microsoft, that significantly reduces computing resources required for training and inference of large-scale models. It provides techniques such as ZeRO (Zero Redundancy Optimizer) for memory optimization, DeepSpeed-MoE for Mixture of Experts, and high-performance inference. Currently at version 0.18.9, it maintains an active development pace with frequent patch releases addressing bug fixes, performance enhancements, and new feature integrations, often every few weeks.","language":"python","status":"active","version":"0.18.9","tags":["deep-learning","pytorch","distributed-training","llm-training","gpu","optimization","hpc"],"last_verified":"Thu May 21","install":[{"cmd":"pip install deepspeed","imports":["import deepspeed\nengine, optimizer, _, _ = deepspeed.initialize(model=model, optimizer=optimizer, config_params=ds_config)","from deepspeed.runtime.engine import DeepSpeedEngine","from deepspeed.ops.adam import DeepSpeedCPUAdam"]},{"cmd":"DS_BUILD_OPS=1 pip install deepspeed --global-option=\"--cuda_ext\" --global-option=\"--multi_tensor_adam\" --global-option=\"--fused_lamb\" --global-option=\"--sparse_attn\" --global-option=\"--fp16\"","imports":[]}],"homepage":"http://deepspeed.ai","github":"https://github.com/deepspeedai/DeepSpeed","docs":"https://deepspeed.readthedocs.io","changelog":null,"pypi":"https://pypi.org/project/deepspeed/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":40,"avg_install_s":72.6,"avg_import_s":17.7,"wheel_type":"sdist"},"url":"https://checklist.day/v1/registry/deepspeed/compatibility"}}