jangkyung / cube-studio

cube studio开源云原生一站式机器学习/深度学习AI平台，支持sso登录，多租户/多项目组，数据资产对接，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式算法训练，超参搜索，推理服务VGPU，多集群调度，边缘计算，serverless，标注平台，自动化标注，数据集管理，大模型一键微调，llmops，私有知识库，AI应用商店，支持模型一键开发/推理/微调，私有化部署，支持国产cpu/gpu/npu芯片，支持RDMA，支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/spark/ray/volcano分布式

Cube Studio

English | 简体中文

Infra

cube-studio is a one-stop cloud-native machine learning platform open sourced by Tencent Music, Currently mainly includes the following functions

• 1、data management: feature store, online and offline features; dataset management, structure data and media data, data label platform
• 2、develop: notebook(vscode/jupyter); docker image management; image build online
• 3、train: pipeline drag and drop online; open template market; distributed computing/training tasks, example tf/pytorch/mxnet/spark/ray/horovod/kaldi/volcano; batch priority scheduling; resource monitoring/alarm/balancing; cron scheduling
• 4、automl: nni, ray
• 5、inference: model manager; serverless traffic control; tf/pytorch/onnx/tensorrt model deploy, tfserving/torchserver/onnxruntime/triton inference; VGPU; load balancing、high availability、elastic scaling
• 6、infra: multi-user; multi-project; multi-cluster; edge cluster mode; blockchain sharing;

Doc

https://github.com/tencentmusic/cube-studio/wiki

WeChat group

learning、deploy、consult、contribution、cooperation, join group, wechart id luanpeng1234 remark<open source>, construction guide

Job Template

tips:

• 1、You can develop your own template, Easy to develop and more suitable for your own scenarios

template	type	describe
linux	base	Custom stand-alone operating environment, free to implement all custom stand-alone functions
datax	import export	Import and export of heterogeneous data sources
hadoop	data processing	hdfs,hbase,sqoop,spark client
sparkjob	data processing	spark serverless
volcanojob	data processing	volcano multi-machine distributed framework
ray	data processing	python ray multi-machine distributed framework
ray-sklearn	machine learning	sklearn based on ray framework supports multi-machine distributed parallel computing
xgb	machine learning	xgb model training and inference
tfjob	deep learning	Multi-machine distributed training of tensorflow
pytorchjob	deep learning	Multi-machine distributed training of pytorch
horovod	deep learning	Multi-machine distributed training of horovod
paddle	deep learning	Multi-machine distributed training of paddle
mxnet	deep learning	Multi-machine distributed training of mxnet
kaldi	deep learning	Multi-machine distributed training of kaldi
tfjob-train	model train	distributed training of tensorflow: plain and runner
tfjob-runner	model train	distributed training of tensorflow: runner method
tfjob-plain	model train	distributed training of tensorflow: plain method
tf-model-evaluation	model evaluate	distributed model evaluation of tensorflow2.3
tf-offline-predict	model inference	distributed offline model inference of tensorflow2.3
model-register	model service	register model to platform
model-offline-predict	model service	distributed offline model inference of framework
deploy-service	model service	deploy inference service
media-download	multimedia data processing	Distributed download of media files
video-audio	multimedia data processing	Distributed extraction of audio from video
video-img	multimedia data processing	Distributed extraction of pictures from video
object-detection-on-darknet	machine vision	object-detection with darknet yolov3

Deploy

wiki

Company