Get started with Verta in 5 minutes.
There are a few options:
If you are on Verta Core or Verta Enterprise, you do not need to set up a Verta Server; please reach out to Verta Support for instructions for your server information.
You are only looking to run open-source ModelDB, head over to the ModelDB repo for installation instructions.
The Verta client supports Python 2.7 & 3.5–3.8!
# via pippython -m pip install verta
Python 2.7 & 3.6–3.8 is supported through conda, as well.
# via condaconda install verta -c conda-forge
On Verta Enterprise, log into the Verta Web App (e.g., https://app.verta.ai) and visit the Profile page to find your developer key.
If using ModelDB open-source, you will not require any special credentials
from verta import Clientclient = Client(HOST, email=VERTA_EMAIL, dev_key=VERTA_DEV_KEY)
proj = client.set_project("Fraud Detection")expt = client.set_experiment("Recurrent Neural Net")
run = client.set_experiment_run("Two-Layer Dropout LSTM")run.log_hyperparameter("num_layers", 2)run.log_hyperparameter("hidden_size", 512)run.log_hyperparameter("dropout", 0.5)
Now that you have versioned a few models, you can interact with them in a variety of ways:
Build dashboards on the Verta Web App based on the models
Merge, branch, and manage all changes to your models
Share your models and reports with your organization or publicly
Deploy versioned models via Verta Deployment and Monitoring