Model registry overview#
With the Neptune model registry, you can store your models in a central location and collaboratively manage their lifecycle. This enables stakeholders and applications to access your models for various purposes, such as audits, tests, or stage management.
You can use Neptune to manage your models in the following ways:
- Create models and track generic model metadata, such as the model signature and validation dataset.
- Create versions of your models:
- Log parameters and other metadata that might change from one version to another.
- Track or store model binaries.
- Track the performance of specific model versions.
- Manage stage transitions of model versions, using four available stages.
- Query and download stored model files and metadata, through the app or API.
How it works#
Similar to the Run
object, you initialize and work with a Model
object. This puts the data in the Models tab of your project.
Then, for each model, you create versions as you refine the model, using ModelVersion
objects. This lets you store and track specific model metadata separately from your experimentation runs.
In the example screenshot below, you can see five logged versions of a model that represents a pre-trained classification model.
See example model registry in Neptune 
API reference pages#
init_model()
functionModel
classinit_model_version()
functionModelVersion
class