{"data":{"slug":"kleveross-ormb","name":"ormb","tagline":"Docker for ML/DL Models Based on OCI Artifacts","github_url":"https://github.com/kleveross/ormb","owner":"kleveross","repo":"ormb","owner_avatar_url":"https://avatars.githubusercontent.com/u/68282154?v=4","primary_language":"Go","stars":473,"forks":61,"topics":["docker","docker-registry","harbor","image-registry","machine-learning","model-management","model-versioning","oci","oci-artifacts","oci-registry","opencontainers"],"archived":false,"github_pushed_at":"2024-01-26T02:53:43+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/kleveross-ormb","markdown_url":"https://www.graphcanon.com/tools/kleveross-ormb.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/kleveross-ormb","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=kleveross-ormb","description":"Docker for Your ML/DL Models Based on OCI Artifacts","homepage_url":null,"license":"Apache-2.0","open_issues":32,"watchers":16,"ai_summary":"A tool to manage machine learning and deep learning models using Docker and OCI artifacts for model and version management.","readme_excerpt":"## Getting Started\n\nYou can watch our sample usage video or read the text version below.\n\n\n\nFirst, 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?))\n\n```bash\n\n---\n\n### Install the image registry\n\n`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.\n\n---\n\n### Install `ORMB`\n\nYou can install the pre-compiled binary, or compile from source.\n\n#### Install the pre-compiled binary\n\nDownload the pre-compiled binaries from [the releases](https://github.com/kleveross/ormb/releases) page and copy to the desired location.\n\n#### Compile from source\n\nClone:\n\n```\n$ git clone https://github.com/kleveross/ormb\n$ cd ormb\n```\n\nGet the dependencies:\n\n```\n$ go mod tidy\n```\n\nBuild:\n\n```\n$ make build-local\n```\n\nVerify it works:\n\n```\n$ ./bin/ormb --help\n```","github_created_at":"2020-05-21T02:39:10+00:00","created_at":"2026-07-11T23:31:43.394184+00:00","updated_at":"2026-08-04T00:01:44.035858+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"docker","name":"docker"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"model-management","name":"model-management"},{"slug":"model-versioning","name":"model-versioning"},{"slug":"oci-artifacts","name":"oci-artifacts"}],"trust":{"provenance":{"is_fork":false,"github_id":265737190,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-04T00:01:43.331Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":920,"last_release_at":"2022-02-07T02:10:18Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":201,"high_count":0,"last_scan_at":"2026-07-11T23:31:50.894Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-04T00:01:43.763Z"},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-08-04T00:01:43.763Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-04T00:01:43.763Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["If you need sophisticated version control for your ML/DL models through an image registry, ORMB provides this functionality.","For operations where integration with Harbor or other OCI-compatible registries is preferred over traditional storage methods."],"when_not_to_use":["Should you seek simple models deployment without extensive version management features, ORMB may introduce unnecessary complexity.","If your project strictly avoids using Docker and OCI artifacts for model handling, then this tool would not be suitable."],"source":"enrich:decision_facts","observed_at":"2026-07-17T05:20:10.234Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"ORMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management."}]}}