mirror/cube-studio
2
0
Fork 0
mirror of https://github.com/tencentmusic/cube-studio.git synced 2024-11-27 05:33:10 +08:00
Code Issues Packages Projects Releases Wiki Activity
313 Commits 2 Branches 21 Tags 405 MiB
JavaScript 56%
Jupyter Notebook 26.5%
Python 12.1%
TypeScript 3.3%
Less 0.7%
Other 1.3%
28df8a4f19
Go to file
FerdinandWard 28df8a4f19 add sidecar and service monitoring
2022-08-19 16:45:59 +08:00
docs delete kfserving 2022-08-18 15:15:14 +08:00
images fix readme 2022-08-18 15:16:10 +08:00
install add sidecar and service monitoring 2022-08-19 16:45:59 +08:00
job-template add coredns config 2022-08-18 19:30:49 +08:00
myapp add sidecar and service monitoring 2022-08-19 16:45:59 +08:00
.gitignore add docker-compose up mysql 2022-08-08 17:10:55 +08:00
CONTRIBUTING.md Create CONTRIBUTING.md 2022-08-12 15:00:29 +08:00
LICENSE Update LICENSE 2021-11-15 16:48:59 +08:00
README_CN.md Update README_CN.md 2022-08-16 16:46:10 +08:00
README.md Update README.md 2022-08-16 16:45:51 +08:00

README.md

Cube Studio

English | 简体中文

Infra

image

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, katib, 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
media-download data processing Distributed download of media files
video-audio data processing Distributed extraction of audio from video
video-img data processing Distributed extraction of pictures from video
sparkjob data processing spark serverless
ray data processing python ray multi-machine distributed framework
volcano data processing volcano multi-machine distributed framework
xgb machine learning xgb model training and inference
ray-sklearn machine learning sklearn based on ray framework supports multi-machine distributed parallel computing
pytorchjob-train model train Multi-machine distributed training of pytorch
horovod-train model train Multi-machine distributed training of horovod
tfjob model train Multi-machine distributed training of tensorflow
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
kaldi-train model train Multi-machine distributed training of kaldi
tf-model-evaluation model evaluate distributed model evaluation of tensorflow2.3
tf-offline-predict model inference distributed offline model inference of tensorflow2.3
model-offline-predict model inference distributed offline model inference of framework
deploy-service model deploy deploy inference service

Deploy

wiki

cube

Contributor

algorithm: @hujunaifuture @jaffe-fly @JLWLL @ma-chengcheng @chendile

platform: @xiaoyangmai @VincentWei2021 @SeibertronSS @cyxnzb @gilearn @wulingling0108