Model artifact
A model artifact is a persisted file or package containing a trained machine-learning model or supporting assets, parameters, configuration, or metadata needed to reconstruct, run, or deploy it.
Machine Learning Platform Engineering
A model artifact type is a KFP artifact type representing a trained machine-learning model and its framework-specific metadata.
- How it is used
- Passes trained models between KFP pipeline components while supporting framework-specific metadata and lineage.
- How deep it goes
- Shows typed training and validation components and model paths, but does not specify a required model file layout.
- Examples
- Uses a component that saves a trained model and a YOLO validator that loads best.pt and logs mAP.
- What you can do after
- Apply it via KFP annotations to produce a trained model and pass it into a validation component.
Read how Machine Learning Platform Engineering explains model artifact →
Designing Deep Learning Systems: A guide for software engineers
A persisted file containing the data required to reconstruct or execute a trained machine learning model.
- How it is used
- Supports model serving by packaging the files and metadata needed to locate, initialize, cache, and execute a trained model.
- How deep it goes
- Descends to file layout, manifest fields, model initialization, caching, and inference lookup, but not artifact-building procedures.
- Examples
- Uses model.pth, vocab.pth, manifest.json, shared storage, gRPC prediction, and a model manager as concrete artifacts and serving components.
- What you can do after
- Operate/configure a predictor that resolves model identifiers, loads matching artifacts, caches initialized models, and serves inference requests.
Read how Designing Deep Learning Systems: A guide for software engineers explains model artifact →
Related concepts
- GPT4Allused by · GPT4All is an open-source software ecosystem for running and interacting with language models locally on consumer or organizational hardware.
- local aiused by · Local AI is artificial-intelligence computation performed by a model on a user's device or other locally controlled infrastructure rather than through a remote service.
- model repositorypart of · A model repository is a storage system containing machine-learning models and associated versions, artifacts, metadata, or configuration.
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