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SkillsMP has collected 12 skills from open-edge-platform/geti. Open a skill to review its source and details.
Showing 12 of 12 collected skills.
Develop and validate changes in `application/ui/` for the React and TypeScript frontend. Use when touching `application/ui/src/**`, frontend tests, RSBuild or Vitest config, Playwright setup, package scripts, or generated API typings under `src/api`. Helps…
Develop and validate changes in `application/backend/` for the FastAPI `geti` service. Use when touching `application/backend/app/**`, backend tests, backend packaging, backend configuration, API routers, schemas, services, repositories, or database code, or…
Update documentation (README, CHANGELOG, Sphinx docs, or inline docstrings) to reflect changes, fixes, or new features. Use when a PR modifies behavior that should be documented for users or developers.
Regenerate and validate the OpenAPI contract between `application/backend/` and `application/ui/`. Use when backend endpoints, schemas, request or response models, or API surface change, or when `application/ui/src/api/openapi-spec.json` or…
Use the Geti application end to end through its REST API — the project → dataset → annotate → train → deploy pipeline served by the FastAPI backend in `application/backend/`. Use when a user (not a contributor) wants to create a project, upload media, add…
Develop and validate changes in `library/` for the `getitune` Python package (the Geti training library). Use when touching `library/src/**`, `library/tests/**`, `library/pyproject.toml`, recipes, model manifests, or any Python API, CLI, model, training,…
Discover which models, recipes, and tasks the getitune library (the Geti training library) supports before training. Use when a user asks what models are available, how to list recipes, how to filter by task or name pattern, how `list_models(...)` and…
Export a trained getitune model (the Geti training library) to a deployable format. Use when a user wants to run `engine.export(...)` or `getitune export`, choose between OpenVINO IR and ONNX, set FP32 vs FP16 precision with `ExportFormat` / `Precision`, or…
Optimize an exported getitune model (the Geti training library) with post-training quantization. Use when a user wants to run `OVEngine.optimize()` / `engine.optimize()` to produce an INT8 model via NNCF, understands calibration-set requirements, or needs to…
Prepare and point datasets at the getitune library (the Geti training library) for training, testing, and prediction. Use when a user asks which dataset formats are supported, how the `data=` argument of `create_engine(...)` / `--data_root` works, why format…
Run inference and evaluation with a getitune model (the Geti training library). Use when a user wants to call `engine.predict()` / `engine.test()` or `getitune predict` / `getitune test`, run inference with a PyTorch checkpoint versus an exported OpenVINO IR…
Train a computer-vision model with the getitune library (the Geti training library) using its Python API or CLI. Use when a user wants to train, fine-tune, or evaluate a model with `create_engine(...)` and `engine.train()/engine.test()`, run `getitune…