AI engineering glossary · MLOps, LLMOps cloud
What is model artefact?
Model artefact (also called Model artifact): The saved output of training that is needed to use a model: the learned weights, plus configuration, tokenizer, preprocessing objects and metadata. It is stored as files, versioned and loaded by the serving system.
Model artefact: an example
A 14 GB artefact folder holds weights in safetensors format, the tokenizer files and a config.json.
Related terms
- Model registry
- Model serialisation
- Object storage
- Model versioning
More MLOps, LLMOps cloud terms
- Model monitoring
- Model promotion
- Model registry
- Model validation
- Model versioning
- Monitoring
- Multi-stage build
- Observability
Where you learn it
Model artefact is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.