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.
Create a Model
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)
Get a Model
# 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>"))
Delete a model
model.delete()