Using Existing Model

AI/ML Accelerator - MLflow is specifically built to track your ML experiments on the DNAnexus platform environment via the ML JupyterLab (another app in the AI/ML Accelerator package) environment. A license is required in order to use the AI/ML Accelerator package. For more information, please contact DNAnexus Sales via [e-mail].

Once a model has been logged in the DNAnexus project by MLflow, you can load and use it for inference or further evaluation. Below are the instructions for retrieving the model path and loading it for use.

Retrieve the Model Path

When you log a model, MLflow generates a run_ID and stores the model in a specific path. To get the model path, simply click on the model in the 'Artifacts' section of a Run and copy the Path as below.

{alt="The path to the model which is stored in the DNAnexus platform"}

The path to the model which is stored in the DNAnexus platform

Load the Model

Once you have the model path, use the appropriate load_model function to load the model from the specified path. Below are the two examples.

For generic models

loaded_model = mlflow.pyfunc.load_model("<model_path>")
predictions = loaded_model.predict(data)

For framework-specific models (e.g., scikit-learn)

loaded_model = mlflow.sklearn.load_model("<model_path>")
predictions = loaded_model.predict(data)

Resources

Full Documentation

To create a support ticket if there are technical issues:

1. Go to the Help header (same section where Projects and Tools are) inside the platform

2. Select "Contact Support"

3. Fill in the Subject and Message to submit a support ticket.