See Model Guide page for concepts and workflows related to Model product.
A Model is a directory where you can create, manage, and compare a set of Model Runs related to the same machine learning task.
Creates a Model object on the server.
import labelbox from labelbox import Client, Model client = Client(api_key="<YOUR_API_KEY>") model_name = "<your_model_name>" # get ontology_id from a project PROJECT_ID = "<your_project_id>" project = client.get_project(PROJECT_ID) ontology_id = project.ontology().uid # or, get specify ontology_id directly ontology_id = "<your_ontology_id>" client.create_model(name=model_name, ontology_id=ontology_id)
# from model id model = client.get_model("<your_model_id>") all_models = client.get_models() # return all models this user has access to models = client.get_models(where=(Model.name == "<model_name>"))