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Klever Model Registry is a Cloud Native ML model registry. Use Klever Model Registry in order to:
- Manage your ML models
- Version and deliver your ML models with the existing infrastructures
- Keep track of ML models' hyperparameters and so on to help decision makers
- Convert models between different formats ( e.g. TensorFlow SavedModel, ONNX )
- Serve the model
- Get the standalone executable program to deploy ML model inference services on edge devices/servers ( Coming Soon! )
Klever Model Registry's features:
- Deploy with Docker and Kubernetes
- Keep non-Invasive for your business
- Manage ML models like Docker ( With the help of kleveross/ormb )
- Reuse Harbor to store models, without any new infrastructure
- Support model serving for models managed by MLflow
- Extract models signatures for:
- SavedModel
- ONNX
- GraphDef
- NetDef
- Keras H5
- CaffeModel
- TorchScript
- MXNetParams
- PMML
- Convert models from:
- MXNetParams to ONNX
- Keras H5 to SavedModel
- CaffeModel to NetDef
- NetDef to ONNX
See our official documentations for more information。
Clone:
$ git clone https://github.com/kleveross/klever-model-registry
$ cd klever-model-registry
Get the dependencies:
$ go mod tidy
Build:
$ make docker-build
Please have a look at docs/installation.md.
If you want to trial quickly, you can run installation script as follow.
$ wget https://raw.githubusercontent.com/kleveross/klever-model-registry/master/scripts/installation/install-k8s-1.14.sh
$ bash install-k8s-1.14.sh <master-ip>
or
$ wget https://raw.githubusercontent.com/kleveross/klever-model-registry/master/scripts/installation/install-k8s-1.19.sh
$ bash install-k8s-1.19.sh <master-ip>
klever-model-registry project is part of Klever, a Cloud Native Machine Learning platform.
The Klever slack workspace is klever.slack.com. To join, click this invitation to our Slack workspace.