This guide will show you how to register models to Vectice.
The Vectice API enables you to register all models used during development to the Vectice UI. To register your model's data and metadata, use the following Model method to declare your model.
model =Model(name, library, technique, metrics, predictor, attachments)
Once your model is declared, sync the model and its metadata to vectice by assigning the model to your project's phase iteration as follows:
iteration.step_register_model = model
Example
Below is a full example showcasing the concepts mentioned above.
from vectice.models.metric import Metricfrom vectice.models.model import Modelfrom sklearn import ...# Connect to your project by entering your # API Token, endpoint, workspace, and project name.my_project = vectice.connect( api_token="YOUR_API_TOKEN", host="YOUR_ENDPOINT", workspace="YOUR_WORKSPACE", project="YOUR_PROJECT_NAME", )# Retrieve the project phase to begin the model development. phase = my_project.phase("phase one")# Initialize iteration and retrieve the first stepiteration = phase.iteration()# Model metrics and metadatametrics = [Metric("RMSE", 153),Metric("Clusters number", 5)]technique ="clustering"name ="My model"predictor = my_sklearn_predictor# Declaring your model and its metadatamodel =Model(library, technique, metrics, name=name, predictor=my_predictor)# Connecting your model to an iteration will automatically sync the information to Vectice UIiteration.step_register_model = model
For an in-depth example, view the code example found in the Iterative Development guide.