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limitations under the License.

`ORMB` is an open-source model registry to manage machine learning model.

`ORMB` helps you manage your Machine Learning/Deep Learning models with image registry. It makes your models easy to create, version, share and publish.

You can watch our sample usage video or read the text version below.

First, open a model folder that meets the specification of `ORMB`. (See our documentation for more information about [ormbfile.yaml](/docs/README.md#What-is-ormbfile?))

$ tree examples/SavedModel-fashion

examples/SavedModel-fashion

├── model

│   ├── saved_model.pb

│   └── variables

│   ├── variables.data-00000-of-00001

│   └── variables.index

├── ormbfile.yaml

└── training-serving.ipynb

2 directories, 5 files

Next, we can push the trained model from local to remote image registry.

$ ormb save gaocegege/fashion_model:v1

ref: gaocegege/fashion_model:v1

digest: 6b08cd25d01f71a09c1eb852b3a696ee2806abc749628de28a71b507f9eab996

size: 162.1 KiB

format: SavedModel

v1: saved

$ ormb push gaocegege/fashion_model:v1

The push refers to repository [gaocegege/fashion_model]

ref: gaocegege/fashion_model:v1

digest: 6b08cd25d01f71a09c1eb852b3a696ee2806abc749628de28a71b507f9eab996

size: 162.1 KiB

format: SavedModel

v1: pushed to remote (1 layer, 162.1 KiB total)

Taking [Harbor](https://github.com/goharbor/harbor) as an example, we can see the model's metadata in Harbor registry.

<p align="center">

<img src="/docs/images/intro/harbor.png" height="350">

</p>

Then, we can download the model from the registry. The download process is similar to the push.

$ ormb pull gaocegege/fashion_model:v1

v1: Pulling from gaocegege/fashion_model

ref: gaocegege/fashion_model:v1

digest: 6b08cd25d01f71a09c1eb852b3a696ee2806abc749628de28a71b507f9eab996

size: 162.1 KiB

Status: Downloaded newer model for gaocegege/fashion_model:v1

$ ormb export gaocegege/fashion_model:v1

ref: localhost/gaocegege/fashion_model:v1

digest: 6b08cd25d01f71a09c1eb852b3a696ee2806abc749628de28a71b507f9eab996

size: 162.1 KiB

$ tree examples/SavedModel-fashion

examples/SavedModel-fashion

├── model

│   ├── saved_model.pb

│   └── variables

│   ├── variables.data-00000-of-00001

│   └── variables.index

├── ormbfile.yaml

└── training-serving.ipynb

2 directories, 5 files

`ORMB` uses the image registry to store model, you can choose to [install Harbor](https://github.com/goharbor/harbor-helm) or [use Docker Registry](https://docs.docker.com/registry/deploying/). We recommended Harbor here.

See [`ORMB` docs](/docs/README.md) for more information.

* Distribute models with `ORMB` and Docker Registry: [tutorial.md](docs/tutorial.md)

* Serving model with Seldon Core: [tutorial-serving-seldon.md](docs/tutorial-serving-seldon.md)

`ORMB` project is part of Klever, a Cloud Native Machine Learning platform.